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Sentence Transformers v3.3.0 by Hugging Face, Spotting Social Media Anomalies with AI, OpenFLAMEThe top ten nastiest vulnerabilities of Q3Are you exposed? Download the Q3 2024 Vulnerability Watch report to find out.The usual vulns from Microsoft and VMware make the list, but there are some surprises too. Chances are at least one of these vulnerabilities is lurking in your environment. The Watch report outlines the exposure risks and provides actionable steps to mitigate each included CVE, helping reduce your cyber risk. Download the report and stay one step ahead of the most-critical exposure risk.Download nowSponsored🗞️ Welcome to DataPro #120 – Your Weekly Data Science & ML Wizardry! 🌟Get your weekly dose of the freshest DS and ML updates designed to elevate your projects, refine models, and keep you in sync with the latest breakthroughs. From powerful resources to boost model accuracy to emerging trends and practical guides, this edition is packed with insights you won’t want to miss!🔍 Algorithm Spotlight: This Week’s Model Unpacked◘ Optimizing Retrieval in RAG Pipelines with Huggingface Transformers: Discover how reranking can enhance retrieval for RAG.◘ Vision Transformer with BatchNorm: A closer look at Vision Transformer architecture improvements.◘ Fixie AI's Ultravox v0.4.1 Release: Updates and capabilities of Fixie AI's new release.◘ FinSafeNet: Protecting Digital Banking with Deep Learning: From fraud detection to real-time security, see how deep learning is safeguarding finances.◘ Nous Research Debuts Forge Reasoning API Beta & Nous Chat: Explore new tools from Nous Research designed for advanced reasoning and interactive ML models.🚀 What’s Hot: The Next Big ML Trends◘ Pushing the Boundaries of Audio Generation – Google DeepMind: The latest advancements in synthetic audio.◘ Introducing ChatGPT Search: OpenAI integrates search into ChatGPT.◘ AI Text and Synthetic Protein Watermarking: The emerging field of watermarking AI outputs.◘ DeepSeek AI’s JanusFlow: A new framework for cohesive image understanding and generation.◘ TensorOpera AI’s Fox-1 Series: Lightweight models, including the new Fox-1-1.6B series, pushing SLM capabilities.◘ OpenAI’s January Release – Everyday AI Agents: AI agents are soon stepping into daily life automation.🛠️ Tool Talk: ML Platforms Compared◘ Master Data Cleaning in Python – 7 Strategies: Essential tips to refine your data cleaning prowess.◘ Combining Pandas with SQL for Data Analysis: How blending these tools can elevate your data skills.◘ 5 Free Learning Resources for LLM Agents: Perfect for upskilling in large language models.◘ Navigating AI Regulations – Innovation Meets Protection: A dive into balancing AI progress with ethical guardrails.◘ 7 Python Projects to Strengthen Your Data Science Portfolio: Project ideas to showcase and sharpen your skills.📊 Case Files: Success Stories from the ML World◘ Spotting Python Art vs. Multi-Million Dollar Creations: A fascinating test in AI-powered art valuation.◘ AI Takes Center Stage: How AI solutions are finding unique, transformative applications.◘ Excel Reporting’s Hidden Costs – A Fix Guide: Learn how optimized reporting can save resources.◘ Beyond RAG: Precision in Semantic Filtering: Improving precision with refined semantic techniques.◘ Aligning Preferences with AI – For Everyone: Discovering ways to enhance user alignment in AI-driven products.🌍 ML Headlines: Industry Buzz & Discoveries◘ Snowflake & CMU’s SuffixDecoding: A breakthrough in efficient token generation.◘ Sentence Transformers v3.3.0 by Hugging Face: What’s new in the latest release.◘ DeepMind’s AlphaFold 3 – Available Now: Explore the new codebase and on-demand server options.◘ Spotting Social Media Anomalies with AI: A novel approach to detecting volume changes in social data.◘ OpenFLAME by CMU Researchers: A federated, decentralized localization service for better data security.Stay tuned and stay inspired – there’s always something new to discover in the ever-evolving world of Data Science and Machine Learning!Take our weekly survey and get a free PDF copy of our best-selling book,"Interactive Data Visualization with Python - Second Edition."We appreciate your input and hope you enjoy the book!Share Your Insights and Shine! 🌟💬Cheers,Merlyn Shelley,Editor-in-Chief, Packt.📚 Packt Signature Series: Must-Reads & Author Insights➽ RAG-Driven Generative AI: This new title, RAG-Driven Generative AI, is perfect for engineers and database developers looking to build AI systems that give accurate, reliable answers by connecting responses to their source documents. It helps you reduce hallucinations, balance cost and performance, and improve accuracy using real-time feedback and tools like Pinecone and Deep Lake. By the end, you’ll know how to design AI that makes smart decisions based on real-world data—perfect for scaling projects and staying competitive! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $43.99➽ Building Production-Grade Web Applications with Supabase: This new book is all about helping you master Supabase and Next.js to build scalable, secure web apps. It’s perfect for solving tech challenges like real-time data handling, file storage, and enhancing app security. You'll even learn how to automate tasks and work with multi-tenant systems, making your projects more efficient. By the end, you'll be a Supabase pro! Start your free trial for access, renewing at $19.99/month.eBook $15.99 $31.99Print + eBook $39.99➽ Python Data Cleaning and Preparation Best Practices: This new book is a great guide for improving data quality and handling. It helps solve common tech issues like messy, incomplete data and missing out on insights from unstructured data. You’ll learn how to clean, validate, and transform both structured and unstructured data—think text, images, and audio—making your data pipelines reliable and your results more meaningful. Perfect for sharpening your data skills! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $44.99🔍 Model Breakdown: Unveiling the Algorithm of the Week⫸ Reranking Using Huggingface Transformers for Optimizing Retrieval in RAG Pipelines: This article demonstrates how to enhance RAG (Retrieval-Augmented Generation) pipelines with reranking using Huggingface Transformers and Sentence Transformers. By building on a basic RAG setup, the blog covers implementing and evaluating reranking to improve context accuracy and relevance, with linked code examples for easy integration.⫸ Vision Transformer with BatchNorm: This blog explores the impact of incorporating Batch Normalization (BatchNorm) into Vision Transformers (ViTs) to enhance training speed and stability, especially for medium-to-small datasets. Experimental results with MNIST data reveal BatchNorm’s potential benefits over traditional ViTs in faster convergence and resilience with higher learning rates.⫸ Fixie AI Introduces Ultravox v0.4.1: This blog introduces Fixie AI’s Ultravox v0.4.1, an open-source multi-modal AI model designed to enhance real-time conversational AI by reducing latency, improving context-aware interactions, and enabling multi-modal understanding across text, images, and more.⫸ FinSafeNet: Advancing Digital Banking Security with Deep Learning for Fraud Detection and Real-Time Transaction Protection. This blog discusses the rising importance of AI-driven cybersecurity in digital banking, highlighting FinSafeNet, a novel deep-learning model that enhances fraud detection. With optimized feature selection and dual-attention mechanisms, FinSafeNet outperforms traditional models, achieving high accuracy and efficiency in detecting transaction fraud.⫸ Nous Research Introduces Two New Projects: The Forge Reasoning API Beta and Nous Chat. This blog explores Nous Research’s Forge Reasoning API Beta and Nous Chat, both designed to improve AI’s real-time reasoning efficiency. By optimizing inference speed and scalability through the Hermes model, these tools aim to enhance conversational AI with faster, context-aware responses suitable for dynamic applications.🚀 Trendspotting: What's Next in Tech Trends⫸ Pushing the frontiers of audio generation - Google DeepMind: This blog highlights advancements in Google’s speech generation technology, enabling natural, multi-speaker dialogue in digital assistants. With innovations like NotebookLM Audio Overviews and Illuminate, Google enhances AI-driven dialogue with improved audio quality, efficiency, and speaker consistency for immersive, accessible user experiences.⫸ Introducing ChatGPT search: This blog highlights ChatGPT’s enhanced web search feature, offering timely answers with links to reliable sources, covering topics like weather, stocks, news, and more. Available for Plus, Team, and select users, it blends natural conversation with accurate, up-to-date information from trusted providers.⫸ Watermarking for AI Text and Synthetic Proteins: This blog examines the role of digital watermarking in countering misinformation and bioterrorism risks posed by large language models and generative protein design. It highlights watermarking’s potential to trace ownership and enhance security across digital and biological content.⫸ DeepSeek AI Releases JanusFlow: A Unified Framework for Image Understanding and Generation. This blog introduces JanusFlow, a unified AI framework by DeepSeek AI that combines image understanding and generation within a single model. Using a streamlined architecture, JanusFlow enhances multimodal efficiency, outperforming traditional models across various benchmarks without complex modifications.⫸ TensorOpera AI Releases Fox-1: A Series of Small Language Models (SLMs) that Includes Fox-1-1.6B and Fox-1-1.6B-Instruct-v0.1. This blog introduces Fox-1, TensorOpera AI’s efficient Small Language Model (SLM) series, designed to deliver large language model (LLM)-like capabilities with minimal resources. Fox-1’s innovative architecture and open-source accessibility make advanced natural language processing feasible for researchers and developers with limited computational power.⫸ OpenAI's Expected January Launch: AI Agents Set to Automate Everyday Life. This blog covers OpenAI’s upcoming AI agents, set to revolutionize automation by performing autonomous tasks for users. With adaptive learning and context awareness, these agents aim to streamline personal and professional tasks, though privacy and ethical concerns remain.🛠️ Platform Showdown: Comparing ML Tools & Services⫸ 7 Ways to Improve Your Data Cleaning Skills with Python: This blog offers seven essential Python techniques for improving data cleaning skills, focusing on handling invalid data, converting data types, encoding categorical variables, managing outliers, feature selection, scaling, and filling missing values. These methods streamline data preparation for accurate analysis and model building.⫸ Using Pandas and SQL Together for Data Analysis: This blog explains how to combine SQL and Python (via Pandas) for data management, highlighting SQL’s readability and native database handling alongside Python’s flexibility. The tutorial introduces PandaSQL to enable SQL-style querying of Pandas DataFrames, demonstrating streamlined workflows in data analysis.⫸ 5 No-Cost Learning Resources for LLM Agents: This blog highlights five free resources for learning about Large Language Model (LLM) agents, covering courses, bootcamps, and guides that teach foundational concepts, agent architectures, and real-world applications. These resources aim to help beginners and professionals alike stay current in the rapidly evolving field of LLM agents.⫸ Navigating AI Regulation: Balancing Innovation and Protection. This blog highlights five free resources for learning about Large Language Model (LLM) agents, covering courses, bootcamps, and guides that teach foundational concepts, agent architectures, and real-world applications. These resources aim to help beginners and professionals alike stay current in the rapidly evolving field of LLM agents.⫸ 7 Python Projects to Boost Your Data Science Portfolio: This blog outlines seven data science-focused Python projects designed to strengthen programming skills. Projects include automated data cleaning, ETL pipelines, data profiling packages, and CLI tools, all aimed at enhancing Python proficiency through real-world applications and best practices.📊 Success Stories: Real-World ML Case Studies⫸ Can You Tell Free Python Art from Multi-Million Dollar Pieces? This blog explores using Python for generative art inspired by Piet Mondrian and Josef Albers, focusing on creating unique, reproducible pieces. The author shares techniques for controlled randomness and color theory, encouraging readers to try their hand at generative art with accessible coding tools.⫸ Nobody Puts AI in a Corner! This blog explains how companies can effectively transform into AI-enabled businesses by learning from past digitalization and data science efforts. Through two anecdotes, it illustrates how a successful AI transformation requires integrating AI into core business functions, fostering cross-team communication, and leveraging industry knowledge to identify meaningful applications rather than relying solely on isolated AI initiatives.⫸ Reporting in Excel Could Be Costing Your Business More Than You Think — Here’s How to Fix It… This blog shares solutions to common reporting challenges faced by agencies, such as lengthy data compilation, limited Excel capabilities, and data inaccuracies. It outlines a workflow using Python in Deepnote for data cleaning, BigQuery for secure and efficient data storage, and Power BI for dynamic, interactive visualizations, streamlining the reporting process and enhancing data insights.⫸ Beyond RAG: Precision Filtering in a Semantic World. This blog delves into improving Retrieval-Augmented Generation (RAG) systems by incorporating outlier detection for efficient and accurate question filtering. Highlighting the limitations of standard retrieval methods, it introduces "Muzlin," a Python library for semantic filtering, to ensure questions align with available context, optimizing RAG performance in production environments.⫸ Preference Alignment for Everyone! This blog provides a detailed guide to Reinforcement Learning from Human Feedback (RLHF) as a method for preference alignment (PA) in large language models. By aligning model outputs with user preferences through human feedback, RLHF enhances user satisfaction, making AI interactions more relevant and reliable. The post includes practical implementation tips using tools like Hugging Face and Amazon SageMaker, offering readers a hands-on, replicable approach to integrating PA in AI systems.🌍 ML Newsflash: Latest Industry Buzz & Discoveries⫸ Researchers from Snowflake and CMU Introduce SuffixDecoding: This blog introduces SuffixDecoding, a model-free approach designed to speed up large language model (LLM) token generation. By leveraging suffix tree structures built from past outputs and current prompts, SuffixDecoding efficiently predicts and verifies token continuations without the need for draft models or additional decoding heads. This method improves throughput and reduces latency, proving valuable for complex applications like multi-stage pipelines and chat systems.⫸ Hugging Face Releases Sentence Transformers v3.3.0: This blog discusses Hugging Face's release of Sentence Transformers v3.3.0, highlighting advancements in CPU efficiency, prompt-based training, and model scalability. The update enhances NLP accessibility, making high-performance deployment feasible on resource-limited devices.⫸ DeepMind Released AlphaFold 3 Inference Codebase, Model Weights and An On-Demand Server: This blog discusses DeepMind’s release of AlphaFold 3, which extends structure prediction beyond proteins to multiple biomolecules, enabling broad research access and precision in drug discovery, biomolecular interactions, and therapeutic development with reduced computational barriers.⫸ Detecting Anomalies in Social Media Volume Time Series: This blog discusses using a residual-based approach to detect anomalies in social media conversation volumes, using Twitter data as an example. It covers seasonal adjustment, residual analysis, and real-time detection for effective social media monitoring.⫸ CMU Researchers Propose OpenFLAME: A Federated and Decentralized Localization Service. This blog introduces OpenFLAME, a decentralized, federated mapping service for indoor and private spaces that leverages DNS for scalable, privacy-preserving localization. It enables precise, adaptable localization without relying on centralized mapping providers.We’ve got more great things coming your way—see you soon!*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{font-size:75%;line-height:0} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}}

Summarize Texts Using the BART Model with Hugging Face Transformers, Fine-Tune T5 for QnA💥 FREE AI & ChatGPT Workshop (Limited time Offer) 🤯An AI-powered professional will earn 10x more. 💰An AI-powered founder will build & scale his company 10x faster 🚀An AI-first company will grow 50x more! 📊🚀Join this 3-hour AI Workshop (worth $399) - FREE for DataPro readers to learn AI strategies & hacks to 10X work output and grow your business.🗓️ Tomorrow | ⏱️ 10 AM ESTWith AI & Chatgpt, you will be able to:✅ Make smarter decisions based on data in seconds using AI✅ Automate daily tasks and increase productivity & creativity✅ Skyrocket your business growth by leveraging the power of AI✅ Save 1000s of dollars by using ChatGPT to simplify complex problems👉 Hurry! Click here to register (FREE for First 100 people only) 🎁Sponsored🗞️ Welcome to DataPro #119 – Your Weekly Data Science & ML Digest! 🌟Stay ahead in the world of AI and ML with this week’s top insights, strategies, and tools to elevate your projects and optimize performance. Here’s what’s trending:🔍 Model Spotlight: This Week’s Algorithm Insight★ Mastering Summarization: A guide to summarizing text with BART using Hugging Face Transformers.★ No-Code Wins: Discover the best no-code LLM app builders to streamline your workflows.★ Fresh Toolkit: Hugging Face’s new SmolTools—what you need to know.★ 3D Tracking Game-Changer: DELTA—an AI method that’s 10x faster at pixel tracking in 3D from monocular videos.★ Next-Level Embeddings: NVIDIA AI introduces MM-Embed.🚀 Exclusive for Packt Community: 50% Off Generative AI in Action!Join 25+ top AI experts and access 30+ sessions at our flagship event (Nov 11-13, LIVE). Public tickets are at 35% off, but you get 50% off—our best rate!Limited seats available prices rise by $200 once they're gone. Don’t wait!Book Now with Code BIGSAVE50🚀 Trending Now: Future Tech and Beyond★ T5 Fine-Tuning: How to fine-tune T5 for question answering tasks with Hugging Face Transformers.★ Understanding AI: A quick look at ANI, AGI, and ASI—three core types of artificial intelligence.★ Blueprints for Innovation: Create up-to-date generative AI apps with real-time vector embedding for Amazon MSK.★ Fish Agent Release: Check out Fish Agent v0.1 3B.★ Defense Llama: Scale AI and Meta’s new security initiative.🛠️ Tool Comparisons: ML Platforms Head-to-Head★ Critical Thinking Skills: 7 essential skills every data scientist needs.★ AI Regulation Guide: Navigating the fine line between innovation and protection.★ Meta’s AdaCache: A fresh tool for optimizing AI workflows.★ Model Depot: LLMWare’s latest contribution to model management.★ Hunyuan Model: Tencent’s powerful Hunyuan-MoE-A52B.★ AMD Goes Open Source: Details on the AMD OLMo release.📊 Case Studies: Real-World ML in Action★ MDAgents: A multi-agent framework enhancing medical decision-making with large language models.★ SMART Filtering: Improving NLP model evaluation with enhanced benchmarking.★ Hertz-Dev: Explore the open-source 8.5B audio model for real-time conversational AI.★ PII Masker: An essential open-source tool for safeguarding sensitive data.★ Scalable Chatbots: Building a context-aware chatbot using Amazon DynamoDB, Bedrock, and LangChain.🌍 ML Newsflash: Industry Highlights★ Free Learning Opportunity: Unlimited access to 365 Data Science courses until Nov 21.★ Python Certification: Learn Python and become a certified data analyst for free this week.★ Run Model Streamer: Run AI’s new open-source tool explained.★ MaskGCT: Dive into this state-of-the-art text-to-speech model.★ PyTorch/XLA 2.5 Updates: What’s new?★ BigQuery Prep Simplified: Meet the new AI-driven data preparation tool.Stay informed and inspired with DataPro’s latest curation—boost your skills, stay ahead, and make an impact!Take our weekly survey and get a free PDF copy of our best-selling book,"Interactive Data Visualization with Python - Second Edition."We appreciate your input and hope you enjoy the book!Share Your Insights and Shine! 🌟💬Cheers,Merlyn Shelley,Editor-in-Chief, Packt.📚 Packt Signature Series: Must-Reads & Author Insights➽ RAG-Driven Generative AI: This new title, RAG-Driven Generative AI, is perfect for engineers and database developers looking to build AI systems that give accurate, reliable answers by connecting responses to their source documents. It helps you reduce hallucinations, balance cost and performance, and improve accuracy using real-time feedback and tools like Pinecone and Deep Lake. By the end, you’ll know how to design AI that makes smart decisions based on real-world data—perfect for scaling projects and staying competitive! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $43.99➽ Building Production-Grade Web Applications with Supabase: This new book is all about helping you master Supabase and Next.js to build scalable, secure web apps. It’s perfect for solving tech challenges like real-time data handling, file storage, and enhancing app security. You'll even learn how to automate tasks and work with multi-tenant systems, making your projects more efficient. By the end, you'll be a Supabase pro! Start your free trial for access, renewing at $19.99/month.eBook $15.99 $31.99Print + eBook $39.99➽ Python Data Cleaning and Preparation Best Practices: This new book is a great guide for improving data quality and handling. It helps solve common tech issues like messy, incomplete data and missing out on insights from unstructured data. You’ll learn how to clean, validate, and transform both structured and unstructured data—think text, images, and audio—making your data pipelines reliable and your results more meaningful. Perfect for sharpening your data skills! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $44.99🔍 Model Breakdown: Unveiling the Algorithm of the Week⇝ How to Summarize Texts Using the BART Model with Hugging Face Transformers: This blog guides readers on using BART, a powerful tool for summarizing long texts into concise versions. It covers setting up the environment with Hugging Face Transformers and loading the model to create coherent summaries efficiently.⇝ Best No-Code LLM App Builders: This post highlights three open-source, no-code solutions—Flowise AI, Langflow, and Dify—that enable non-technical users to easily build and deploy AI applications using drag-and-drop interfaces and seamless integration with various LLMs.⇝ Hugging Face Releases SmolTools: This article explores Hugging Face's latest release of Smol-Tools, showcasing the compact yet powerful SmolLM2 model. It highlights the model's ability to perform efficient NLP tasks like summarization and rewriting while ensuring accessibility and performance.⇝ DELTA: A Novel AI Method that Efficiently (10x Faster) Tracks Every Pixel in 3D Space from Monocular Videos. This article covers DELTA, a novel method by UMass Amherst & MIT-IBM Watson AI Lab for efficient dense 3D tracking in videos. DELTA outperforms existing approaches by leveraging spatio-temporal attention and upsampling, achieving faster, more accurate results.⇝ NVIDIA AI Introduces MM-Embed: This article discusses NVIDIA's MM-Embed, a groundbreaking multimodal retriever achieving state-of-the-art results by handling text and image content seamlessly. MM-Embed improves cross-modal search performance, setting new standards for diverse, real-world information retrieval tasks.🚀 Trendspotting: What's Next in Tech Trends⇝ How to Fine-Tune T5 for Question Answering Tasks with Hugging Face Transformers: This article explains how to fine-tune the T5 model, a versatile text-to-text transformer, for question answering tasks using the Hugging Face and PyTorch libraries. It also guides readers through installing necessary tools and loading datasets.⇝ The Three Different Types of Artificial Intelligence – ANI, AGI and ASI: This article explains the three main types of AI: Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Super Intelligence (ASI). It covers their capabilities, challenges, and potential impacts on technology and society.⇝ Build up-to-date generative AI applications with real-time vector embedding blueprints for Amazon MSK: This article explores building real-time AI applications using Amazon Bedrock and Amazon MSK to create vector embeddings, stored in OpenSearch Service, enabling Retrieval Augmented Generation (RAG). It emphasizes real-time data for accurate, up-to-date generative AI outputs.⇝ Fish Agent v0.1 3B Released: This article discusses Fish Agent v0.1 3B, a breakthrough Text-to-Speech system addressing complex linguistic challenges with its Dual Autoregressive architecture and Firefly-GAN vocoder. It bypasses G2P conversion, enhancing multilingual capabilities and delivering natural-sounding, high-quality speech synthesis.⇝ Scale AI and Meta Introduces Defense Llama: This article introduces Defense Llama, a collaborative project by Scale AI and Meta, designed as the first LLM for U.S. national security. It integrates specialized defense data, enhancing threat detection, secure communication, and strategic analysis capabilities.🛠️ Platform Showdown: Comparing ML Tools & Services⇝ 7 Critical Thinking Skills Needed in Data Science: This article lists and explains seven critical thinking skills essential for data scientists. It covers analytical abilities like pattern recognition and systems thinking, as well as practical skills such as problem decomposition and impact assessment for effective data analysis.⇝ Navigating AI Regulation: Balancing Innovation and Protection: This article highlights the need for balanced AI regulation that ensures ethical practices, privacy, and accountability without stifling innovation. It discusses challenges like algorithmic bias, data privacy, and safety risks, emphasizing global cooperation and risk-based frameworks for effective policies.⇝ Meta AI Introduces AdaCache: This article covers AdaCache, a training-free method developed by Meta AI and Stony Brook University to optimize video generation in diffusion transformers. By using adaptive caching and motion-based regularization, AdaCache enhances processing speed while maintaining high-quality output, addressing latency challenges efficiently.⇝ LLMWare Introduces Model Depot: This blog introduces LLMWare.ai’s Model Depot on Hugging Face, showcasing over 100 optimized Small Language Models (SLMs) for Intel PCs. It highlights support for OpenVINO and ONNX formats, enabling efficient, secure, on-device AI development and deployment.⇝ Tencent Releases Hunyuan-Large (Hunyuan-MoE-A52B) Model: This blog introduces Tencent's Hunyuan-Large, the largest open-source Transformer-based Mixture of Experts (MoE) model, featuring 389 billion parameters. It excels in NLP tasks and long-context processing, offering significant advancements in efficiency and scalability for the AI community.⇝ AMD Open Sources AMD OLMo: This blog discusses AMD's release of OLMo, a fully open-source 1B-parameter language model trained on AMD GPUs. It emphasizes OLMo's capabilities in NLP tasks, accessibility for developers, and its potential to democratize AI research and innovation.📊 Success Stories: Real-World ML Case Studies⇝ MDAgents: A Dynamic Multi-Agent Framework for Enhanced Medical Decision-Making with Large Language Models. This blog discusses MDAgents, a multi-agent framework developed by MIT, Google Research, and Seoul National University Hospital for medical decision-making. MDAgents dynamically assign LLMs based on task complexity, improving diagnostic accuracy across medical benchmarks through adaptive collaboration.⇝ SMART Filtering: Enhancing Benchmark Quality and Efficiency for NLP Model Evaluation. This blog covers SMART filtering, developed by Meta AI, Pennsylvania State University, and UC Berkeley, for improving NLP benchmark datasets by removing easy, contaminated, or redundant examples. This method enhances dataset quality, reduces computational costs, and maintains reliable model performance metrics for better evaluations.⇝ Meet Hertz-Dev: An Open-Source 8.5B Audio Model for Real-Time Conversational AI. This blog introduces Hertz-Dev, an open-source 8.5 billion parameter model for real-time conversational AI by Standard Intelligence Lab. It achieves low latency on a single RTX 4090 GPU, making high-performance audio modeling accessible and efficient for diverse developers.⇝ Meet PII Masker: An Open-Source Tool for Protecting Sensitive. This blog introduces PII Masker, an advanced open-source tool by HydroXai for protecting sensitive data using AI and NLP. It automates the detection and masking of PII, ensuring privacy compliance while maintaining data usability and minimizing false positives.⇝ Build a scalable, context-aware chatbot with Amazon DynamoDB, Amazon Bedrock, and LangChain: This blog outlines how to build scalable, context-aware chatbots using Amazon DynamoDB, LangChain, and Amazon Bedrock. It details managing chat history with DynamoDB for seamless user interactions and creating intelligent responses through LangChain's integration, ensuring coherent and personalized conversations.🌍 ML Newsflash: Latest Industry Buzz & Discoveries⇝ Free Data and AI Courses with 365 Data Science—Unlimited Access until Nov 21: This blog highlights 365 Data Science's annual free access initiative, providing users with unrestricted learning resources, expert-led courses, and certifications to enhance career prospects in data science and AI. It aims to democratize education and bridge the skills gap in a competitive job market.⇝ Learn Python and get Certified as a Data Analyst for Free this Week! This blog highlights DataCamp's Free Access Week from November 4th to 10th, offering users unlimited learning at no cost. It features popular courses for data analysis and science in Python and R, providing opportunities for certification and skill-building in data analytics.⇝ Run AI Open Sources Run:ai Model Streamer: This blog highlights Run AI's release of Model Streamer, an open-source tool designed to drastically reduce model loading times by up to six times. It supports various storage solutions and simplifies deployment, enhancing productivity and the efficiency of real-world AI applications.⇝ MaskGCT: A New Open State-of-the-Art Text-to-Speech Model. This blog introduces MaskGCT, an innovative open-source TTS model that overcomes traditional alignment and duration prediction challenges using a non-autoregressive, two-stage framework. Trained on 100,000 hours of data, it excels in naturalness, speed, and versatile applications like voice cloning and emotional synthesis.⇝ What’s new with PyTorch/XLA 2.5: This blog discusses the updates in PyTorch/XLA 2.5, including API streamlining for easier use with PyTorch, improvements to the torch_xla.compile function for better debugging, and experimental TPU support in vLLM. These changes enhance the developer experience and broaden deployment capabilities.⇝ Introducing AI-driven BigQuery data preparation: This blog introduces BigQuery data preparation, an AI-powered solution that simplifies data preparation by automating tasks like data cleansing and transformation. It features visual data pipelines and AI-driven suggestions, enhancing efficiency and ensuring reliable, actionable insights for users in Google Cloud.We’ve got more great things coming your way—see you soon!*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{font-size:75%;line-height:0} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}}

Gemini Models Hit GitHub Copilot, Python One-Liners for Data Cleaning, Python for Proximity Mapping200+ hours of research on AI tools & hacks packed in 3 hoursThis free 3-hour Training on AI & ChatGPT (worth $399) will help you become a master of 20+ AI tools & prompting techniques and save 16 hours/week.Get it now for absolutely free! (for first 100 users only) 🎁You will learn how to:➣ Build business that make $10,000 by just using AI tools➣ Make quick & smarter decisions using AI-led data insights➣ Write emails, content & more in seconds using AI➣ Solve complex problems, research 10x faster & save 16 hours every weekRegister & save your seat now! (100 free seats only)SponsoredWelcome to DataPro #118 – Your Weekly Data Science & ML Wizardry! 🌟Stay sharp in the fast-evolving world of data science with this week’s essential strategies, tools, and trends. We’ve handpicked the best to supercharge your projects, refine accuracy, and amp up performance. Ready for this week’s power-ups? Let’s go!🚨 Packt Conference Alert! 🚨Stay at the forefront of AI innovation! 🚀 Join us for 3 action-packed days of LIVE sessions with 20+ top experts and unleash the full power of Generative AI at our upcoming conference. Don’t miss out - Claim your spot today!🔍 Algorithm Insight: Model of the Week Unveiled➣Gemini Models Hit GitHub Copilot: Dive into code generation like never before with Gemini models, now integrated in GitHub Copilot through Google Cloud’s partnership.➣SimpleQA from OpenAI: A new benchmark tool to measure the factual accuracy of language models.➣Theory of Mind in AI: Evaluating the latest with SimpleToM, a new tool testing language models’ understanding of human perspectives.➣Meta AI’s LongVU: Tackling long video comprehension with a new multimodal language model.➣JetBrains Introduces CoqPilot: A Plugin for LLM-Based Proof Generation.➣Jupyter Releaser: Streamlining software releases for Jupyter tools just got easier.🚀 Tech Trend Radar: What's Making Waves?➣LLMs for Chunked Retrieval: How to leverage LLMs for smarter, chunk-based information recall.➣OmniParser by Microsoft AI: Convert UI screenshots to structured data on Hugging Face.➣Hawkish 8B Financial Model: Outperforming in finance tests, this model aces CFA Level 1 exams.➣Gen-AI Safety Stack: A guide to safety strategies for text-to-image model applications.➣Equation Solving in Python: A must-read on closed-form versus numerical solutions.🛠️ Tool Time: Comparing Platforms & Services➣Cohere’s Aya Expanse: A powerful multilingual model suite closing the language gap in AI.➣Meta AI’s NotebookLlama: An open-source alternative to Google’s NotebookLM, now available.➣AI for Screen Interaction: Explore Claude 3.5’s new screen navigation capabilities.➣Text Embeddings with Amazon RDS & Bedrock: Seamlessly embed and retrieve text data from Amazon RDS using Amazon’s Bedrock.➣Custom Observability Solution: Track, log, and improve generative AI applications with Bedrock.📊 Real-World Impact: Success Stories & Case Studies➣Python One-Liners for Data Cleaning: 10 concise solutions for everyday data wrangling.➣2024’s Top Python Libraries: Must-have Python tools for data science this year.➣Automating Model Selection with LLMs: Streamlining model testing and tuning.➣5 Tips to Optimize Language Models: Quick techniques for better model performance.➣Lessons Beyond AI: Three crucial takeaways from a recent data science conference.🌍 ML Newsflash: Industry Discoveries & Updates➣Hugging Face Models on Mobile: A step-by-step guide to deploying Hugging Face models on mobile.➣Python for Proximity Mapping: Learn how to create distance maps in Python for quick insights.➣Data Leakage Alert: Key practices to prevent leaks during data preprocessing.➣In-Depth RAG Guide: Understand Retrieval Augmented Generation with a breakdown of each component.➣Beyond Basic Attention in Transformers: Analyzing positional embedding techniques for improved model accuracy.Dive into this week’s DataPro and stay on top of everything that’s shaping the world of Data Science & Machine Learning!Take our weekly survey and get a free PDF copy of our best-selling book,"Interactive Data Visualization with Python - Second Edition."We appreciate your input and hope you enjoy the book!Share Your Insights and Shine! 🌟💬Cheers,Merlyn Shelley,Editor-in-Chief, Packt.📚 Packt Signature Series: Must-Reads & Author Insights➽ RAG-Driven Generative AI: This new title, RAG-Driven Generative AI, is perfect for engineers and database developers looking to build AI systems that give accurate, reliable answers by connecting responses to their source documents. It helps you reduce hallucinations, balance cost and performance, and improve accuracy using real-time feedback and tools like Pinecone and Deep Lake. By the end, you’ll know how to design AI that makes smart decisions based on real-world data—perfect for scaling projects and staying competitive! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $43.99➽ Building Production-Grade Web Applications with Supabase: This new book is all about helping you master Supabase and Next.js to build scalable, secure web apps. It’s perfect for solving tech challenges like real-time data handling, file storage, and enhancing app security. You'll even learn how to automate tasks and work with multi-tenant systems, making your projects more efficient. By the end, you'll be a Supabase pro! Start your free trial for access, renewing at $19.99/month.eBook $15.99 $31.99Print + eBook $39.99➽ Python Data Cleaning and Preparation Best Practices: This new book is a great guide for improving data quality and handling. It helps solve common tech issues like messy, incomplete data and missing out on insights from unstructured data. You’ll learn how to clean, validate, and transform both structured and unstructured data—think text, images, and audio—making your data pipelines reliable and your results more meaningful. Perfect for sharpening your data skills! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $44.99🔍 Model Breakdown: Unveiling the Algorithm of the Week➽ Gemini Models on GitHub Copilot: GitHub and Google Cloud’s partnership introduces Gemini 1.5 Pro to GitHub, enhancing AI-driven code generation, analysis, and optimization for developers. The Gemini model, with a two-million-token context window, will integrate into GitHub Copilot, Google AI Studio, Vertex AI, and popular IDEs.➽ OpenAI Introduces SimpleQA: AI Benchmark for Measuring the Factuality of Language Models. The blog introduces SimpleQA, a factuality benchmark for evaluating how accurately language models answer short, fact-seeking questions. SimpleQA emphasizes correctness, topic diversity, and difficulty for advanced models. Built with rigorous quality checks, it helps researchers gauge model performance and reduce “hallucinations” in AI responses.➽ SimpleToM: Evaluating Applied Theory of Mind Capabilities in Large Language Models. The blog discusses SimpleToM, a dataset developed to assess Theory of Mind (ToM) in large language models (LLMs) through realistic scenarios. Unlike prior methods, it evaluates nuanced mental state inferences and behavior judgments, revealing gaps in LLMs’ understanding and application of social reasoning in real-world situations.➽ Data Minimization Does Not Guarantee Privacy: The blog explains the data minimization principle in machine learning, emphasizing the need to collect only essential data to reduce privacy risks, as outlined by global data protection laws. It discusses challenges in operationalizing this principle due to inherent data correlations and highlights privacy audits, using adversarial attacks, to identify vulnerabilities.➽ Meta AI Releases LongVU: A Multimodal Large Language Model that can Address the Significant Challenge of Long Video Understanding. The blog highlights Meta AI's release of LongVU, a Multimodal Large Language Model designed to tackle the challenges of long video understanding. By using adaptive compression techniques and cross-modal queries, LongVU reduces redundant frames and tokens, enabling efficient processing of hour-long videos within limited context lengths, thereby advancing video analysis in AI.➽ JetBrains Researchers Introduce CoqPilot: A Plugin for LLM-Based Generation of Proofs. The blog introduces CoqPilot, a VS Code extension from JetBrains that automates Coq proof generation. By using LLMs like GPT-4 and tools like CoqHammer, CoqPilot fills proof gaps, verifies solutions, and replaces incomplete proofs. This integration streamlines proof creation, enhancing efficiency in software reliability and formal verification tasks.➽ Jupyter Releaser: Streamlining Software Releases for the Jupyter Ecosystem. The blog covers Jupyter Releaser, a tool launched by the Jupyter team to streamline release management across Jupyter projects. By automating tasks like changelog creation and artifact publishing via GitHub Actions, Jupyter Releaser reduces errors, speeds up releases, and promotes consistency, benefiting the broader open-source development community.🚀 Trendspotting: What's Next in Tech Trends➽ How and Why to Use LLMs for Chunk-Based Information Retrieval. The article explores using Large Language Models (LLMs) like GPT-4 for chunk-based information retrieval. By utilizing hybrid search techniques—combining term frequency algorithms and vector-based search—LLMs identify relevant text chunks. Despite improving retrieval, issues like irrelevant chunk selection persist, potentially misleading LLM responses in systems like RAG (Retrieval-Augmented Generation).➽ Microsoft AI Releases OmniParser Model on HuggingFace: A Compact Screen Parsing Module that can Convert UI Screenshots into Structured Elements. OmniParser by Microsoft enables GUI interaction for AI by interpreting interface elements from screenshots without HTML or metadata. Using vision-based detection, icon description, and OCR, it enhances AI usability across platforms, boosting accuracy in interface tasks and advancing applications in automation and accessibility.➽ Meet Hawkish 8B: A New Financial Domain Model that can Pass CFA Level 1 and Outperform Meta Llama-3.1-8B-Instruct in Math & Finance Benchmarks. The article introduces Hawkish 8B, a finance-focused AI model excelling in financial analysis and quantitative tasks. With specialized training in economics and market analysis, Hawkish 8B surpasses other models in benchmarks and even passes CFA Level 1, aiding finance professionals.➽ Gen-AI Safety Landscape: A Guide to the Mitigation Stack for Text-to-Image Models: The article covers Text-to-Image (T2I) AI models like Latent Diffusion Models, detailing capabilities like inpainting and associated risks, including generating inappropriate content. It emphasizes a robust safety mitigation stack across training, fine-tuning, and post-deployment to minimize harmful outputs and ethical concerns.➽ Solving Equations in Python: Closed-Form vs Numerical: The article explores when closed-form solutions are possible in mathematical models, such as Kepler’s orbital equation, and why numerical methods are often needed. Using Python’s SymPy, it examines equations to build intuition around solvable forms and complexities that defy simple algebraic solutions.➽ Demystifying Azure Storage Account Network Access: The article details network access control for Azure storage accounts within medallion architecture, focusing on using service endpoints and private endpoints. It explains setup configurations, firewall rules, and network security groups (NSGs) to securely enable data access for virtual machines while preventing unauthorized access.🛠️ Platform Showdown: Comparing ML Tools & Services➽ Cohere for AI Releases Aya Expanse (8B & 32B): A State-of-the-Art Multilingual Family of Models to Bridge the Language Gap in AI. The article introduces Aya Expanse by Cohere for AI, an open-weight, multilingual language model family addressing underrepresentation in NLP. Designed to support low-resource languages, Aya Expanse achieves high accuracy on multilingual benchmarks, promoting inclusivity and equitable access to AI-driven tools across diverse linguistic communities.➽ Meta AI Silently Releases NotebookLlama: An Open Version of Google's NotebookLM. The article introduces Meta's NotebookLlama, an open-source alternative to Google’s NotebookLM, integrating LLMs into a notebook interface for accessible, scalable data analysis and documentation. NotebookLlama offers customizable deployment, enhances code-writing and documentation, and empowers the AI community with a flexible, community-driven tool.➽ Computer Use and AI Agents: A New Paradigm for Screen Interaction: The article explores recent advancements in multimodal AI agents from Anthropic, Microsoft, and Apple. These agents enhance computer and mobile screen interaction using technologies like Anthropic’s Claude 3.5, Microsoft’s OmniParser, and Apple’s Ferret-UI, highlighting varied approaches for parsing screens and performing actions, albeit with ongoing challenges.➽ Embed textual data in Amazon RDS for SQL Server using Amazon Bedrock: The article explains how to generate vector embeddings from Wikipedia data stored in an Amazon RDS SQL Server database. Using Amazon Bedrock and Amazon SageMaker, the solution integrates embeddings into SQL Server for similarity search in generative AI applications, streamlining analysis through AWS’s managed AI services.➽ Empower your generative AI application with a comprehensive custom observability solution: The article introduces an observability and evaluation solution for Amazon Bedrock to enhance generative AI applications. By integrating decorators in application code, this solution captures logs and metrics, supporting Retrieval Augmented Generation (RAG) evaluations and enabling proactive monitoring, quality improvement, and secure data handling across AI workflows.📊 Success Stories: Real-World ML Case Studies➽ 10 Useful Python One-Liners for Data Cleaning: The article provides Python one-liners for common data cleaning tasks like handling duplicates, validating formats, managing missing values, and scaling numbers. It guides users in cleaning a sample dataset to prepare it for analysis, covering essentials like email validation, date standardization, and whitespace trimming.➽ 10 Essential Python Libraries for Data Science in 2024: The article covers ten essential Python libraries for data science, each specializing in a critical task like data collection (Scrapy), manipulation (pandas), visualization (Matplotlib), machine learning (scikit-learn), and deployment (Flask). These libraries streamline end-to-end workflows, making data science more accessible and efficient.➽ Selection and Experimentation Automation with LLMs: The article demonstrates how to automate model selection and experimentation using large language models (LLMs). By applying LLMs like GPT-4 with Scikit-Learn, the code automates model evaluation, selects the best-performing model, and even suggests hyperparameters for tuning. This approach streamlines model experimentation in data science.➽ 5 Tips for Optimizing Language Models: The article provides five essential tips for optimizing language models: using prompt engineering to refine model responses, applying Retrieval Augmented Generation (RAG) for contextual accuracy, fine-tuning for task specificity, adjusting hyperparameters to enhance performance, and compressing models for efficiency and accessibility across various platforms.➽ Three Crucial Data Lessons That I Learned from a Data Conference That’s Not Related to AI. The article shares insights from a data conference, emphasizing cost control, effective data translation, and cross-department collaboration to boost data team ROI. Practical tips include using cost-monitoring dashboards, fostering data literacy, and aligning data projects with strategic business goals.➽ How Prefab scales with Spanner’s PostrgeSQL interface: Prefab uses Google Cloud Spanner’s PostgreSQL interface for its impressive scalability, simplicity, and cost-effectiveness. Spanner offers the robustness of PostgreSQL with high availability, strong ACID compliance, and horizontal scaling, making it ideal for Prefab's feature flagging and dynamic logging services.🌍 ML Newsflash: Latest Industry Buzz & Discoveries➽ How to Deploy Hugging Face Models on Mobile Devices: This guide covers deploying Hugging Face models on mobile by converting models like DistilBERT into ONNX format, then quantizing to reduce file size for mobile compatibility. The article also demonstrates testing and setup for Android deployment, enabling efficient and scalable use of machine learning on mobile devices.➽ Building Interactive Data Science Applications with Python:This article details building interactive data science applications using Python libraries like Streamlit, Gradio, Dash, and Panel. It explains creating engaging apps with features like user inputs, feedback, and multimedia elements, and includes an example dashboard that visualizes U.S. population data from 2010–2019.➽ How to Make Proximity Maps with Python: This blog post walks through creating a "distance from" map using Python to calculate distances between universities in the Southeastern Conference (SEC) for college football. It details coding steps to visualize travel distances from one school to others on a contour map, ideal for analyzing team travel or other location-based data.➽ Data Leakage in Preprocessing: This article addresses data leakage in machine learning, where test data unintentionally influences training data during preprocessing. Common issues include imputing missing values using the mean of the entire dataset, blending test insights into training, which skews model performance.➽ The Ultimate Guide to RAGs — Each Component Dissected: This blog explores Retrieval Augmented Generation (RAG) in Large Language Models, where relevant data is first retrieved from external sources, then combined with user queries to produce more accurate responses. The RAG approach helps improve accuracy, reduce hallucinations, and provide up-to-date information efficiently.➽ Beyond Attention: How Advanced Positional Embedding Methods Improve upon the Original Approach in Transformer Architecture. This article explains how the Transformer architecture improved AI models by enabling faster processing and capturing long-range relationships in data through self-attention. Positional embeddings, like sinusoidal and learned encodings, help maintain order, making models work well across different data types.We’ve got more great things coming your way—see you soon!*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{font-size:75%;line-height:0} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}}

Product-Oriented ML, ML Metamorphosis, Optimize ALBERT for Mobile Deployment with Hugging Face Trans🚀 The Most Awaited 2-for-1 Deal Drops Tomorrow! 🚀Unlock our 2-for-1 offer at Generative AI in Action (Nov 11-13) and bring a friend, colleague, or your team to double the learning experience.🗓 Sale Starts: Tomorrow, Friday, Oct 25, 10 AM ET⏳ Duration: 24 hours onlyDon’t miss out—mark your calendar and get ready to grab this exclusive deal!CTA: Join 25+ AI Experts, 30+ Sessions & 1000+ Tech ProsWelcome to DataPro #117 – Your Weekly Data Science & ML Wizardry! 🌟Stay on top of AI and ML breakthroughs with this week’s hottest tools, trends, and strategies. Ready to supercharge your projects? Let’s jump in! 🚀🔍 Model of the Week: Cracking Open AI Innovations✦ Activation Steering by Microsoft: Discover a game-changing method to enhance instruction-following in LLMs.✦ Stable Diffusion 3.5: The latest release from Stability AI promises faster, more accurate image generation.✦ FunnelRAG: Supercharge your AI with this innovative approach to improve retrieval in RAG systems.✦ Meet SynPO: A cutting-edge technique using synthetic data for smarter model alignment.✦ Moonshine: Fast, accurate, lightweight speech recognition for edge devices.🚀 Tech Trends on the Rise✦ LayerSkip by Meta AI: Speed up LLM inference with this breakthrough in AI architecture.✦ IBM’s Granite 3.0 Models: Power your enterprise AI with these robust new models.✦ OMat24 Dataset by Meta AI: The biggest open inorganic materials dataset, ready for your next project.✦ Meta Spirit LM: Explore the future of text and speech with this open-source multimodal model.✦ Generative AI in Retail: How AI and data are transforming customer experiences.🛠️ Tools & Techniques Showdown✦ 5 Hidden Data Transformation Gems: Unveil new techniques for cleaner, faster analysis.✦ Top 10 GitHub Repos for NLP: Essential resources to master natural language processing.✦ Generative AI for Devs: Speed up software development with AI-driven coding tools.✦ Optimizing ALBERT for Mobile: Learn how to deploy Hugging Face Transformers efficiently on mobile.✦ Streamline Teamwork with Monday.com: Unlock smoother collaboration for data science projects.📊 Real-World Wins: ML Success Stories✦ OpenAI & Lenfest Fellowship: Learn how AI is shaping the future of journalism.✦ ML Metamorphosis: Discover how chaining models leads to breakthrough results.✦ Key Roles in Fraud Prediction: A deep dive into the people behind successful fraud detection with ML.✦ Mastering Back-of-the-Envelope Math: Quick estimations for better data-driven decisions.✦ Building Product-Oriented ML: From concept to product—guidance for data scientists.✦ Amazon Q Developer for AWS Lambda: New tools for faster, smarter code development.🌍 ML Newsflash: Hot Off the Press✦ The AWS Bedrock Tutorial: Everything you need to set up for AWS success.✦ Relational Deep Learning for Self-Service AI: Make ML easier with relational databases.✦ Why Scaling Works: Insights on inductive biases vs. scaling up models.✦ Optimizing AI Models on AWS Inferentia & Trainium: Best practices for faster results.✦ Chunking Documents with LLMs: Unlocking knowledge, one chunk at a time.Stay sharp, stay curious, and stay ahead with DataPro!Take our weekly survey and get a free PDF copy of our best-selling book,"Interactive Data Visualization with Python - Second Edition."We appreciate your input and hope you enjoy the book!Share Your Insights and Shine! 🌟💬Cheers,Merlyn Shelley,Editor-in-Chief, Packt.📚 Packt Signature Series: Must-Reads & Author Insights➽ RAG-Driven Generative AI: This new title, RAG-Driven Generative AI, is perfect for engineers and database developers looking to build AI systems that give accurate, reliable answers by connecting responses to their source documents. It helps you reduce hallucinations, balance cost and performance, and improve accuracy using real-time feedback and tools like Pinecone and Deep Lake. By the end, you’ll know how to design AI that makes smart decisions based on real-world data—perfect for scaling projects and staying competitive! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $29.99 $43.99➽ Building Production-Grade Web Applications with Supabase: This new book is all about helping you master Supabase and Next.js to build scalable, secure web apps. It’s perfect for solving tech challenges like real-time data handling, file storage, and enhancing app security. You'll even learn how to automate tasks and work with multi-tenant systems, making your projects more efficient. By the end, you'll be a Supabase pro! Start your free trial for access, renewing at $19.99/month.eBook $15.99 $31.99Print + eBook $27.98 $39.99➽ Python Data Cleaning and Preparation Best Practices: This new book is a great guide for improving data quality and handling. It helps solve common tech issues like messy, incomplete data and missing out on insights from unstructured data. You’ll learn how to clean, validate, and transform both structured and unstructured data—think text, images, and audio—making your data pipelines reliable and your results more meaningful. Perfect for sharpening your data skills! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $30.99 $44.99🔍 Model Breakdown: Unveiling the Algorithm of the Week➽ Microsoft AI Introduces Activation Steering: A Novel AI Approach to Improving Instruction-Following in Large Language Models. This blog discusses the limitations of large language models in following detailed instructions during text generation and introduces "activation steering," a new method that improves adherence to constraints without retraining models, enhancing their flexibility and precision.➽ Stability AI Releases Stable Diffusion 3.5: Stable Diffusion 3.5 Large and Stable Diffusion 3.5 Large Turbo. This blog covers the release of Stable Diffusion 3.5, highlighting its improved image generation capabilities, adaptability for different user needs, and efficiency on consumer hardware. It emphasizes Stability AI’s focus on accessibility through flexible variants and permissive licensing.➽ FunnelRAG: A Novel AI Approach to Improving Retrieval Efficiency for Retrieval-Augmented Generation. This blog introduces Retrieval-Augmented Generation (RAG) and its role in enhancing language models by integrating external knowledge sources. It highlights FunnelRAG, a progressive retrieval method that improves efficiency and accuracy by refining data in stages, addressing challenges in large-scale information retrieval.➽ Meet SynPO: A Self-Boosting Paradigm that Uses Synthetic Preference Data for Model Alignment. This blog discusses SynPO (Synthetic Preference Optimization), a technique for improving LLMs' alignment with human preferences using self-generated synthetic data. SynPO reduces reliance on human annotations, enabling scalable, iterative improvement in model performance through synthetic feedback loops.➽ Moonshine: A Fast, Accurate, and Lightweight Speech-to-Text Models for Transcription and Voice Command Processing on Edge Devices. This blog discusses the introduction of Moonshine speech recognition models, which outperform traditional models like Whisper by using a variable-length encoder to reduce latency and computational demands. These models are faster, more efficient, and highly accurate, even on low-resource devices.🚀 Trendspotting: What's Next in Tech Trends➽ Meta AI Releases LayerSkip: A Novel AI Approach to Accelerate Inference in Large Language Models (LLMs). This blog introduces LayerSkip, a novel solution for accelerating large language model inference. It combines layer dropout, early exit loss, and self-speculative decoding to reduce computational and memory demands while maintaining high accuracy, offering significant efficiency improvements for practical AI deployment.➽ IBM Releases Granite 3.0 2B and 8B AI Models for AI Enterprises: This blog introduces IBM's Granite 3.0 AI models, designed for enterprises seeking secure, adaptable, and transparent AI solutions. These models excel in natural language processing, offer enhanced decision-making, and integrate with IBM's watsonx platform, making them ideal for privacy-focused, efficient AI deployment in diverse enterprise environments.➽ Meta AI Releases Meta’s Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models: This blog discusses the release of Meta's Open Materials 2024 (OMat24) dataset, containing over 110 million DFT calculations, and the EquiformerV2 model, which excels in predicting material properties. These resources aim to accelerate AI-driven materials discovery, addressing challenges in global issues like climate change and next-generation computing.➽ Meta AI Releases Meta Spirit LM: An Open Source Multimodal Language Model Mixing Text and Speech: This blog highlights Meta Spirit LM, an open-source multimodal language model that integrates text and speech at the word level, addressing expressivity limitations in traditional TTS systems. With its ability to generate natural and emotion-driven speech, it represents a significant leap in AI-driven multimodal applications, including conversational agents and virtual assistants.➽ How generative AI and data are redefining retail experiences? This blog discusses how generative AI is revolutionizing the retail and consumer goods industry by improving customer service, automating product marketing, and enabling hyper-personalized shopping experiences. Companies like TVG, DoorDash, and Orbit Irrigation are leveraging AI tools like Amazon Bedrock to enhance operations, drive growth, and improve customer satisfaction.🛠️ Platform Showdown: Comparing ML Tools & Services➽ 5 Lesser-Known Data Transformation Techniques for Better Analysis: This blog covers five lesser-known data transformation techniques—Box-Cox, Yeo-Johnson, Rank, Reciprocal, and Binning transformations—that can enhance data analysis by improving normality, managing outliers, and reducing skewness. These techniques offer more flexibility and precision for various data preprocessing tasks.➽ 10 GitHub Repositories to Master Natural Language Processing (NLP): This blog explores ten essential GitHub repositories for mastering Natural Language Processing (NLP). These repositories provide valuable resources such as tutorials, frameworks, courses, and projects to help users build and improve NLP models, including popular libraries like Hugging Face's Transformers, spaCy, and more.➽ Generative AI for Software Development - DeepLearning.AI: This blog highlights the "Generative AI for Software Development" course, led by former Google AI lead Laurence Moroney. The course equips developers with skills to integrate generative AI tools like GitHub Copilot and ChatGPT into real-world software development. Learners will enhance coding efficiency, improve code quality, and develop innovative solutions through hands-on projects. By mastering Large Language Models (LLMs), participants can streamline their development workflow and earn a Skill Certificate from DeepLearning.AI, demonstrating their proficiency in using AI-powered tools.➽ How to Optimize ALBERT for Mobile Deployment with Hugging Face Transformers: This blog tutorial guides you through optimizing the ALBERT model for mobile deployment by using techniques like quantization, pruning, and converting the model to ONNX format. These methods help reduce model size, improve performance, and enhance efficiency on resource-limited mobile devices, while maintaining high accuracy.➽ Streamlining Data Science Projects: How to Use Monday.com for Efficient Team Collaboration. This article discusses how Monday.com can streamline project management for data science teams by offering a centralized platform for collaboration, tracking progress, and managing workflows. It helps teams stay organized by integrating tools like GitHub and Slack, providing real-time data tracking, and enabling custom visual workflows. Monday.com's automation features, transparency, and flexibility in adapting to agile approaches make it a game-changer for teams handling multiple data projects simultaneously.📊 Success Stories: Real-World ML Case Studies➽ OpenAI and the Lenfest Institute AI Collaborative and Fellowship program: This blog discusses the collaboration between The Lenfest Institute, OpenAI, and Microsoft to support local journalism through AI-driven business sustainability. Selected newsrooms will receive grants and AI fellows to implement AI technologies and share innovations across the industry.➽ ML Metamorphosis: Chaining ML Models for Optimized Results. This blog explores the concept of "ML metamorphosis," a process that improves machine learning model performance by chaining multiple models together. Techniques like knowledge distillation, model compression, and rule extraction help create more efficient and accurate models.➽ Key Roles in a Fraud Prediction Project with Machine Learning: This blog explains the various roles involved in developing machine learning projects, such as project managers, fraud analysts, data engineers, data scientists, and MLOps engineers, and how their collaboration ensures the successful implementation and delivery of ML solutions.➽ Mastering Back-of-the-Envelope Math Will Make You a Better Data Scientist: This blog explores how quick-and-dirty estimates, like Enrico Fermi’s during the first nuclear bomb test, can be valuable in decision-making. It emphasizes structured thinking, simplicity, and getting "accurate enough" results for business decisions.➽ Product-Oriented ML: A Guide for Data Scientists. This blog outlines how to plan successful machine learning (ML) projects by defining clear problem statements, aligning with business goals, setting functional and non-functional requirements, and fostering cross-functional collaboration to avoid common pitfalls in ML development.➽ Introducing the new Amazon Q Developer experience in AWS Lambda: This blog highlights the integration of Amazon Q Developer, an AI-powered assistant, into AWS Lambda’s new code editor. The tool offers real-time code suggestions, chat assistance, and troubleshooting features to enhance coding efficiency and streamline debugging for developers.🌍 ML Newsflash: Latest Industry Buzz & Discoveries➽ The AWS Bedrock Tutorial I Wish I Had: Everything You Need to Know to Prepare Your Machine for AWS Infrastructure. This blog introduces a multi-part series on building full-stack AI apps with AWS Bedrock, React, and Node.js. It guides readers through AWS setup, permissions, and integrating GenAI tools for creating a fully functional language translation app.➽ Self-Service ML with Relational Deep Learning. This blog introduces Relational Deep Learning (RDL), an approach that bypasses traditional feature engineering by learning directly from relational databases. It explores RDL's potential in complex, real-world datasets, highlighting its strengths and challenges.➽ Why Scaling Works: Inductive Biases vs The Bitter Lesson. This blog explores the power of scaling in deep learning, demonstrating how larger models with more data consistently outperform others in tasks like image generation and language modeling, illustrated through a toy spiral classification problem.➽ AI Model Optimization on AWS Inferentia and Trainium: This blog discusses optimizing machine learning workloads on AWS Inferentia chips using the AWS Neuron SDK, focusing on performance improvements in training models like Vision Transformers through PyTorch, OpenXLA, and Neuron-specific techniques.➽ Efficient Document Chunking Using LLMs: Unlocking Knowledge One Block at a Time. This article explains how to use large language models (LLMs) like GPT-4o to chunk documents into meaningful segments, where each chunk represents a unified idea, aiding efficient knowledge base creation and organization.We’ve got more great things coming your way—see you soon!*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{line-height:0;font-size:75%} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}}

Limited-time offer: Elevate your skills and knowledge with savings on our best-selling books! @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} } @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} }👋 Hello ,✨Welcome to Packt’s Signature Series: New Titles Just Arrived!📚We're thrilled to introduce the latest addition to our Signature Series—a curated collection of the best-selling titles in the data industry! This limited-time offer is packed with expert insights on mastering data science algorithms, Generative AI, and multimodal systems.For a limited time, enjoy a 30% discount on both ebook and print editions of these recommended titles. Don’t delay—this offer ends soon!Don't miss this opportunity to upskill and elevate your career. Ready to dive in?➽ Cracking the Data Science Interview: Master essential skills such as Python, SQL, and machine learning while gaining confidence in explaining complex concepts. 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Tackle challenges in domain organization, data contracts, and analytics architecture, enabling effective governance and implementation of a collaborative analytics platform in Azure Cloud. Start your free trial for access, renewing at $19.99/month.eBook $27.98 $39.99Print + eBook $34.98 $49.99➽ Python Data Cleaning Cookbook - Second Edition: Learn advanced data preprocessing and cleaning techniques for machine learning and NLP models using Python. Utilize updated AI tools for effective data cleaning, monitor and validate large datasets, and diagnose issues using cutting-edge methodologies for improved analytical outcomes. Start your free trial for access, renewing at $19.99/month.eBook $27.98 $39.99Print + eBook $39.98 $49.99➽ Data Stewardship in Action: Cultivate the mindset and skills for effective data stewardship through practical advice and best practices in governance, quality management, and compliance. 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Implement Python libraries like DoWhy, Pandas, and Prophet in real-world scenarios, enhancing strategies and driving data-driven decision-making for effective marketing efforts.➽Learn Microsoft Fabric: Explore Microsoft Fabric's features through real-world examples to build robust data analytics solutions, including lakehouses and data warehouses. Learn to monitor and manage your analytics system for flexibility, performance, and security, while leveraging AI-driven insights with Copilot integration.➽Microsoft Power BI Cookbook - Third Edition: Dive into Microsoft Data Fabric to enhance data strategies and gain deeper insights. Effortlessly create Hybrid tables and comprehensive scorecards while utilizing new visualization tools that transform complex data into clear, actionable charts and reports for effective decision-making in Power BI.➽Getting Started with DuckDB: Utilize DuckDB to efficiently load, transform, and query diverse data sources and formats. Gain hands-on experience with SQL, Python, and R for data analysis, while exploring how open-source tools and cloud services enhance DuckDB’s versatile capabilities in the data ecosystem.➽Fundamentals of Analytics Engineering: Explore how analytics engineering aligns with your organization's data strategy while gaining insights from seven industry experts. Address common challenges faced by businesses and learn to implement scalable analytics solutions, from data ingestion to visualization, using industry-leading tools.We’ve got more great things coming your way—see you soon! *{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{line-height:0;font-size:75%} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}} @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} } @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} }

40+ Cool AI Tools, Inheritune, Rhymes AI’s Aria, Create Podcasts with NotebookLM, Falcon 2 11BLooking to build, train, deploy, or implement Generative AI?Meet Innodata — offering high-quality solutions for developing and implementing industry-leading generative AI, including:➤ Diverse Golden Datasets➤ Supervised Fine-Tuning Data➤ Human Preference Optimization (e.g. RLHF)➤ RAG Development ➤ Model Safety, Evaluation, & Red Teaming ➤ Data Collection, Creation, & Annotation ➤ Prompt Engineering With 5,000+ in-house SMEs and expansion and localization supported across 85+ languages,Innodata drives AI initiatives for enterprises globally.Learn More!SponsoredWelcome to DataPro #116 – Your Weekly Dose of Data Magic! 🌟Stay at the cutting edge of data engineering, data science, and AI! This week’s newsletter delivers the latest tools, insights, and strategies you need to accelerate your workflow, fine-tune your models, and power your innovations. From optimizing pipelines to mastering AI trends, we’ve got you covered. Let’s get started! 🚀🚨 Packt Conference Alert! 🚨Stay at the forefront of AI innovation! 🚀 Join us for 3 action-packed days of LIVE sessions with 20+ top experts and unleash the full power of Generative AI at our upcoming conference. Don’t miss out - Claim your spot today!🔍 Spotlight Algorithm: This Week's Must-Know Model✦ Un Ministral, des Ministraux: Mistral AI’s new Ministral 3B and 8B models✦ MIBench: The Ultimate AI Benchmark for Model Inversion Attacks & Defenses✦ OPEN-RAG: Revolutionizing Reasoning with Open-Source LLMs✦ Inheritune: Smarter, Smaller Language Models with Efficient AI Training✦ OpenAI’s MLE-Bench: A Deep Dive into ML Engineering Agent Performance✦ OpenAI Update: Disrupting Misuse and Strengthening AI Ethics🚀 Tech Buzz: What’s Trending in AI?✦ BigQuery x Apache Iceberg: Next-Gen Data Storage, Unlocked✦ Meet Arch: The Intelligent Gateway for Seamless LLM Integration✦ MRAG-Bench: A Vision-Centric AI Benchmark for Multimodal Models✦ Adaptive Computation: MIT's Smarter, Cost-Efficient Language Models✦ LoLCATS: Stanford’s Efficient LLM Linearization Breakthrough🛠️ Tool Time: Top ML Tools & Services✦ 40+ Cool AI Tools You Can't Miss in October✦ Zyphra's Zamba2-7B: Power-Packed Small Language Model✦ OpenR: An Open-Source Framework for LLM Reasoning✦ SuperNova-Medius: A 14B Model Shaking Up AI✦ Aria: Rhymes AI’s State-of-the-Art Multimodal MoE Model📊 ML in Action: Success Stories✦ NVIDIA’s MoE Models: Upcycling LLMs for Greater Efficiency✦ Google’s Tx-LLM: Fine-Tuned AI for Therapeutic Advancements✦ INTELLECT-1: Pioneering Decentralized AI Model Training✦ HyperAgent: FPT AI’s Generalist Agent Excelling in Software Engineering🌍 ML Newsflash: Fresh Off the AI Press✦ Create Podcasts with NotebookLM: Your Educational Content, Now Audio!✦ YouTube Study Guides: Turn Videos into Learning Powerhouses with NotebookLM✦ Claude AI: A Deep Dive into Anthropic’s AI Assistant & Artifacts✦ ML Deployment 101: Cloud vs. Edge—Which Strategy Wins?✦ lintsampler: Quick Sampling from Any Distribution, Simplified✦ Falcon 2 11B on EC2: A Guide to Efficient Model InferenceThere you have it—this week's freshest insights to keep you ahead in the ever-evolving world of Data and ML! Keep innovating, stay curious, and we’ll see you next week with more DataPro magic! 🎩✨Take our weekly survey and get a free PDF copy of our best-selling book,"Interactive Data Visualization with Python - Second Edition."We appreciate your input and hope you enjoy the book!Share Your Insights and Shine! 🌟💬Cheers,Merlyn Shelley,Editor-in-Chief, Packt.BOOK TODAY AT $239.99 $399.99JoinGenerativeAI InActionnow withaFull Event Pass for just $239.99—40% off the regular price—with codeFLASH40.Three Reasons Why You Cannot Miss This Event:1. Network with 25+ Leading AI Experts2. Gain Insights from 30+ Dynamic Talks and Hands-On Sessions3. Engage with Experts and Peers through 1:1 Networking, Roundtables, and AMAsAct fast—this FLASH SALE is only for a limited number of seats!CLAIM NOW - LIMITED SEATS📚 Packt Signature Series: Must-Reads & Author Insights➽ RAG-Driven Generative AI: This new title, RAG-Driven Generative AI, is perfect for engineers and database developers looking to build AI systems that give accurate, reliable answers by connecting responses to their source documents. It helps you reduce hallucinations, balance cost and performance, and improve accuracy using real-time feedback and tools like Pinecone and Deep Lake. By the end, you’ll know how to design AI that makes smart decisions based on real-world data—perfect for scaling projects and staying competitive! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $29.99 $43.99➽ Building Production-Grade Web Applications with Supabase: This new book is all about helping you master Supabase and Next.js to build scalable, secure web apps. It’s perfect for solving tech challenges like real-time data handling, file storage, and enhancing app security. You'll even learn how to automate tasks and work with multi-tenant systems, making your projects more efficient. By the end, you'll be a Supabase pro! Start your free trial for access, renewing at $19.99/month.eBook $15.99 $31.99Print + eBook $27.98 $39.99➽ Python Data Cleaning and Preparation Best Practices: This new book is a great guide for improving data quality and handling. It helps solve common tech issues like messy, incomplete data and missing out on insights from unstructured data. You’ll learn how to clean, validate, and transform both structured and unstructured data—think text, images, and audio—making your data pipelines reliable and your results more meaningful. Perfect for sharpening your data skills! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $30.99 $44.99🔍 Model Breakdown: Unveiling the Algorithm of the Week➽ Un Ministral, des Ministraux: Mistral AI introduces Ministral 3B and 8B models for edge computing, excelling in knowledge, reasoning, and efficiency. Designed for low-latency, privacy-first use cases, they support up to 128k context length, outperforming competitors while offering compute-efficient solutions for diverse applications.➽ MIBench: A Comprehensive AI Benchmark for Model Inversion Attack and Defense. The postdiscusses Model Inversion (MI) attacks, where attackers attempt to recreate sensitive training data from machine learning models. To address the lack of reliable benchmarks for comparing attacks and defenses, researchers introduced MIBench, a modular toolbox for evaluating MI methods, promoting more consistent, extensible research.➽ OPEN-RAG: A Novel AI Framework Designed to Enhance Reasoning Capabilities in RAG with Open-Source LLMs. This blog discusses Open-RAG, a novel framework designed to improve the reasoning and factual accuracy of retrieval-augmented generation (RAG) models using open-source large language models (LLMs). By transforming LLMs into efficient sparse mixture-of-experts models, Open-RAG excels in handling complex reasoning tasks while balancing accuracy and computational efficiency.➽ Inheritune: An Effective AI Training Approach for Developing Smaller and High-Performing Language Models. This blog discusses Inheritune, a method to train smaller, efficient language models by inheriting early layers from larger pre-trained models and progressively expanding them. Inheritune addresses attention degeneration in deeper layers, achieving performance comparable to larger models with fewer layers.➽ OpenAI’s MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering. This blog introduces MLE-bench, a benchmark created by OpenAI to evaluate AI agents' machine learning engineering skills through 75 Kaggle competitions. The top-performing setup achieved a bronze medal level in 16.9% of competitions, with open-source code available for future research.➽ Update from OpenAI on disrupting deceptive uses of AI: This blog highlights OpenAI's efforts to prevent misuse of its models, particularly during global elections, by disrupting over 20 deceptive networks. It emphasizes ongoing work to enhance AI security and share insights with stakeholders and industry peers.🚀 Trendspotting: What's Next in Tech Trends➽ Announcing BigQuery tables for Apache Iceberg: This blog announces BigQuery tables for Apache Iceberg, a fully managed storage engine offering enterprise-level features like autonomous storage optimization and high-throughput streaming ingestion. It addresses challenges with open-source formats, enabling seamless data management and integration with Apache Spark and Flink.➽ Meet Arch: The Intelligent Layer 7 Gateway for LLM Applications. This blog introduces Arch, an intelligent Layer 7 gateway designed to enhance security, observability, and personalization for large language model (LLM) applications. Arch helps developers efficiently manage sensitive data, track performance, and personalize user interactions in real-time.➽ Researchers from UCLA and Stanford Introduce MRAG-Bench: An AI Benchmark Specifically Designed for Vision-Centric Evaluation for Retrieval-Augmented Multimodal Models. This blog introduces MRAG-Bench, a vision-centric benchmark designed to evaluate large vision-language models (LVLMs) in scenarios where visual knowledge outperforms textual information. It highlights gaps in current models' ability to leverage visual data, encouraging better multimodal understanding.➽ This AI Paper by MIT Introduces Adaptive Computation for Efficient and Cost-Effective Language Models: This blog discusses MIT's innovative approach to improve language model efficiency by adapting computation based on input complexity. Their method dynamically allocates resources, reducing computation by up to 50% without sacrificing performance, optimizing tasks in coding, math, and dialogues.➽ Stanford Researchers Propose LoLCATS: A Cutting Edge AI Method for Efficient LLM Linearization. This blog introduces LoLCATS, a method to efficiently linearize large language models by reducing memory and computational costs without sacrificing quality. Through attention transfer and low-rank adaptation, LoLCATS scales models like Llama 3 70B while maintaining high performance.🛠️ Platform Showdown: Comparing ML Tools & Services➽ 40+ Cool AI Tools You Should Check Out (Oct 2024): This blog highlights various AI tools designed to enhance productivity, creativity, and efficiency across multiple domains, including content creation, personalized media, website building, legal advising, business decision-making, and multimodal capabilities, offering innovative, time-saving solutions.➽ Zyphra Releases Zamba2-7B: A State-of-the-Art Small Language Model. Zyphra's newly released Zamba2-7B is a state-of-the-art small language model that outperforms competitors in quality and speed. Designed for environments with hardware limitations, it combines efficiency, innovative architecture, and open-source availability, democratizing advanced AI.➽ OpenR: An Open-Source AI Framework Enhancing Reasoning in Large Language Models. OpenR is an open-source framework designed to enhance large language models' reasoning abilities through reinforcement learning, process supervision, and advanced inference strategies. It improves reasoning performance in tasks like mathematics and coding, providing a collaborative platform for further advancements.➽ Arcee AI Releases SuperNova-Medius: A 14B Small Language Model Built on the Qwen2.5-14B-Instruct Architecture. SuperNova-Medius, a 14B parameter language model from Arcee AI, balances high performance with accessibility by rivaling larger models like 70B counterparts. It combines innovative optimization techniques for cost-effective, efficient deployment, making advanced AI more inclusive and sustainable.➽ Rhymes AI Released Aria: An Open Multimodal Native MoE Model Offering State-of-the-Art Performance Across Diverse Language, Vision, and Coding Tasks. Aria is an open-source multimodal AI model that integrates text, images, and videos, excelling in complex tasks with its fine-grained mixture-of-experts architecture. It offers competitive performance with lower computational costs, filling a critical gap in accessible multimodal AI.📊 Success Stories: Real-World ML Case Studies➽ NVIDIA AI Researchers Explore Upcycling Large Language Models into Sparse Mixture-of-Experts. Researchers from NVIDIA introduced a method to upcycle pre-trained dense models into Mixture of Experts (MoE) models, enhancing capacity and performance without increasing computational costs. Their technique, using virtual group initialization and softmax-then-topK routing, improved model accuracy and efficiency.➽ Google AI Introduces Tx-LLM: A Large Language Model (LLM) Fine-Tuned fromPaLM-2 to Predict Properties of Many Entities that are Relevant to Therapeutic Development. Tx-LLM, introduced by Google Research and DeepMind, is a fine-tuned large language model designed for diverse therapeutic tasks across drug development. Trained on 709 datasets, it excels in combining molecular and text features, outperforming state-of-the-art models in many tasks.➽ INTELLECT-1: The First Decentralized 10-Billion-Parameter AI Model Training. INTELLECT-1, launched by Prime Intellect AI, is a decentralized initiative to train a 10-billion-parameter AI model, inviting global participation. It challenges centralized AI development, promoting inclusivity, transparency, and collaboration in creating open-source artificial general intelligence (AGI).➽ FPT Software AI Center Introduces HyperAgent: A Groundbreaking Generalist Agent System to Resolve Various Software Engineering Tasks at Scale, Achieving SOTA Performance on SWE-Bench and Defects4J. HyperAgent, introduced by FPT Software AI Center, is a multi-agent system designed to handle a wide range of software engineering tasks. It mimics human developer workflows across phases like planning, code editing, and verification, offering generalizability, efficiency, and scalability.🌍 ML Newsflash: Latest Industry Buzz & Discoveries➽ How to Create Custom Educational Podcasts with NotebookLM? NotebookLM, an AI tool by Google, allows users to create podcasts from documents using two AI voices. These voices discuss the document's key points, making it sound like a real conversation. Users can upload content, customize podcasts, and adjust playback options.➽ How to Create YouTube Video Study Guides with NotebookLM? This blog explains how to use NotebookLM to create study guides from YouTube videos. By uploading video links, NotebookLM generates summaries, FAQs, and structured study materials, making it easier for students and educators to organize key points efficiently.➽ Claude AI: Unboxing Anthropic’s LLM-based AI Assistant, Artifacts & Use Cases. This blog introduces Claude AI, an advanced assistant developed by Anthropic. It highlights Claude's key features, including advanced visual reasoning and "artifacts," which are reusable content pieces that enhance collaborative workflows. Claude excels in business-oriented problem-solving and ethical AI interactions.➽ How to Choose the Best ML Deployment Strategy: Cloud vs. Edge? This blog explores the various methods of deploying machine learning models, emphasizing the differences between cloud and edge deployment. It covers cloud deployment methods like API, serverless, and batch processing, as well as edge deployment for native and web applications, offering pros, cons, and real-world examples.➽ lintsampler: a new way to quickly get random samples from any distribution: lintsampler is a Python package that simplifies and efficiently generates random samples from complex probability distributions. It offers an alternative to traditional methods like MCMC (Markov Chain Monte Carlo), providing an easy, fast, and adaptable approach for sampling across various dimensions and use cases.➽ Learn how to deploy Falcon 2 11B on Amazon EC2 c7i instances for model Inference: This blog introduces the Falcon 2 11B foundation model, developed by Technology Innovation Institute (TII), now deployable on Amazon EC2 c7i instances with Intel AMX support. It explores model quantization (INT8 and INT4) using OpenVINO for efficient, cost-effective real-time AI applications on CPUs.We’ve got more great things coming your way—see you soon!*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{line-height:0;font-size:75%} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}}

ChatGPT’s Canvas, AgentPrune, ML Deployment with Docker, Decision Tree Regressor, Domino Data LabNotion for Startups Thousands of startups use Notion as a connected workspace to create and share docs, take notes, manage projects, and organize knowledge—all in one place. We’re offering 6 months of new Plus plans, including unlimited Notion AI so you can try it all for free!Redemption InstructionsTo redeem the Notion for Startups offer:1. Submit an application using our custom link: https://ntn.so/packt and select Packt on the partner list.2. Include our partner key, STARTUP4110P19151.Free 6-Month Notion Plus Access! 🚀 Use Our Packt Partner Key!SponsoredWelcome to DataPro #115 – Your Weekly Data Science & ML Wizardry! 🌟Stay ahead in AI and ML with the latest strategies, tools, and insights. This week, we’re serving up top picks to supercharge your projects, enhance accuracy, and optimize performance. Let’s dive in! 🚀🚨 Packt Conference Alert! 🚨Stay at the forefront of AI innovation! 🚀 Join us for 3 action-packed days of LIVE sessions with 20+ top experts and unleash the full power of Generative AI at our upcoming conference. Don’t miss out - Claim your spot today!🔍 Algorithm Spotlight: Must-Know Models✦ AgentPrune: A cost-saving multi-agent communication framework for LLMs that filters redundant and malicious content.✦ Anthropic's Message Batches API: Efficient, asynchronous query processing at scale.✦ EuroLLM Released: Multilingual models for EU languages, open-weight and powerful.✦ Meta’s MovieGen: Next-gen media foundation models from Meta AI.🚀 Future Trends You Can’t Miss✦ AutoArena: Open-source AI tool for automated GenAI system evaluations.✦ Reverb AI Models: State-of-the-art speech transcription and diarization outperforming top models.✦ ML Deployment with Docker: A step-by-step guide.✦ 10 Critical AI Concepts in 5 Minutes: Your quick learning boost.🛠️ ML Tools Showdown: What’s Hot✦ TxT360 by LLM360: A 15T-token pre-training dataset setting new standards.✦ Google’s Gemma-2-JPN: A finely tuned AI model for Japanese text.✦ Dataplex: Modern data governance for the AI-driven era.✦ London Summit: UK businesses embrace Google Cloud AI solutions.📊 Real-World Wins: ML Case Studies✦ ZODIAC: Revolutionizing cardiology with LLM-powered diagnostics.✦ Canvas: A new collaborative way to write and code with ChatGPT.✦ Decision Tree Regressor: A hands-on visual guide with code.✦ 5 AI Weekend Projects: Fast, fun, and built in Python.✦ Domino Data Lab on AWS: Streamlining AI governance from policy to practice.🌍 Industry Buzz: Latest Discoveries✦ 10 Essential GitHub Features: Don’t miss out on these time-savers.✦ Prompt Caching in LLMs: Unlocking efficiency and intuition.✦ Slack Meets Amazon Q Business: Simplify your internal data sharing.✦ Virgin Media O2 & BigQuery: Streamlined data sharing success.Happy coding, data warriors! 🎯Take our weekly survey and get a free PDF copy of our best-selling book,"Interactive Data Visualization with Python - Second Edition."We appreciate your input and hope you enjoy the book!Share Your Insights and Shine! 🌟💬Cheers,Merlyn Shelley,Editor-in-Chief, Packt.Secure and Simplify: Salesforce Data Protection with RubrikWhat if your Salesforce data was suddenly lost or corrupted? Human errors, accidental deletions, misconfigurations can all contribute to data loss. 1 of 2 SaaS users that did not implement SaaS data protection experienced data loss or corruption in the last 12 months.Check out this exclusive webinar where we reveal Rubrik's new integration with Salesforce, designed to tackle this exact issue.Watch On-DemandSponsored📚 Packt Signature Series: Must-Reads & Author Insights➽ RAG-Driven Generative AI: This new title, RAG-Driven Generative AI, is perfect for engineers and database developers looking to build AI systems that give accurate, reliable answers by connecting responses to their source documents. It helps you reduce hallucinations, balance cost and performance, and improve accuracy using real-time feedback and tools like Pinecone and Deep Lake. By the end, you’ll know how to design AI that makes smart decisions based on real-world data—perfect for scaling projects and staying competitive! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $29.99 $43.99➽ Building Production-Grade Web Applications with Supabase: This new book is all about helping you master Supabase and Next.js to build scalable, secure web apps. It’s perfect for solving tech challenges like real-time data handling, file storage, and enhancing app security. You'll even learn how to automate tasks and work with multi-tenant systems, making your projects more efficient. By the end, you'll be a Supabase pro! Start your free trial for access, renewing at $19.99/month.eBook $15.99 $31.99Print + eBook $27.98 $39.99➽ Python Data Cleaning and Preparation Best Practices: This new book is a great guide for improving data quality and handling. It helps solve common tech issues like messy, incomplete data and missing out on insights from unstructured data. You’ll learn how to clean, validate, and transform both structured and unstructured data—think text, images, and audio—making your data pipelines reliable and your results more meaningful. Perfect for sharpening your data skills! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $30.99 $44.99🔍 Model Breakdown: Unveiling the Algorithm of the Week➽ Agent Prune: A Robust and Economic Multi-Agent Communication Framework for LLMs that Saves Cost and Removes Redundant and Malicious Contents. AgentPrune reduces token consumption in multi-agent systems by pruning redundant spatial and temporal communications. Developed by Tongji University researchers, it maintains accuracy, cuts costs, and enhances robustness against adversarial attacks in GPT-4 models.➽ Anthropic AI Introduces the Message Batches API: A Powerful and Cost-Effective Way to Process Large Volumes of Queries Asynchronously. Anthropic's Message Batches API allows developers to process up to 10,000 queries asynchronously, ideal for bulk tasks. It offers 50% cost savings, 24-hour processing, and supports Claude models for scalable data analysis and content moderation.➽ EuroLLM Released: A Suite of Open-Weight Multilingual Language Models (EuroLLM-1.7B and EuroLLM-1.7B-Instruct) Capable of Understanding and Generating Text in All Official European Union languages. The EuroLLM project, involving multiple institutions, developed multilingual language models to support all EU languages, addressing the English-language bias in AI. EuroLLM-1.7B and EuroLLM-1.7B-Instruct demonstrated strong performance in multilingual tasks and machine translation.➽ Meta AI Unveils MovieGen: A Series of New Advanced Media Foundation AI Models. This blog introduces Meta AI's MovieGen, a cutting-edge media generation suite enabling high-resolution text-to-video, personalized video creation, and advanced audio synthesis, revolutionizing content creation with scalable, high-quality media generation techniques.🚀 Trendspotting: What's Next in Tech Trends➽ AutoArena: An Open-Source AI Tool that Automates Head-to-Head Evaluations Using LLM Judges to Rank GenAI Systems. Kolena AI's AutoArena automates the evaluation of generative AI systems, using LLM judges to provide objective, scalable, and consistent model comparisons. It reduces human effort, costs, and subjectivity, accelerating AI innovation and decision-making.➽ Rev Releases Reverb AI Models: Open Weight Speech Transcription and Diarization Model Beating the Current SoTA Models. This post introduces Rev's Reverb ASR and Diarization models, which offer state-of-the-art accuracy in speech transcription and speaker identification. These models outperform traditional systems, addressing challenges like long-form speech recognition and speaker attribution.➽ Step-by-Step Guide to Deploying ML Models with Docker: This post explains how to deploy machine learning models using Docker, ensuring consistent environments across platforms. It covers setting up Docker, building a model, creating a Dockerfile, and pushing the container to Docker Hub for scalable deployment.➽ 10 Critical AI Concepts Explained in 5 Minutes: This article offers a quick guide to 10 essential AI concepts, covering topics like algorithms, machine learning, generative AI, and responsible AI, providing a foundational understanding of today's AI advancements and ethical considerations.🛠️ Platform Showdown: Comparing ML Tools & Services➽ LLM360 Group Introduces TxT360: A Top-Quality LLM Pre-Training Dataset with 15T Tokens. LLM360's TxT360 is a 15-trillion-token pre-training dataset built from diverse, high-quality sources like FreeLaw and Wikipedia. Rigorous filtering and deduplication ensure clean, coherent data for developing advanced, open-source language models.➽ Google Releases Gemma-2-JPN: A 2B AI Model Fine-Tuned on Japanese Text. Google's new "gemma-2-2b-jpn-it" model is a Japanese-focused, decoder-only LLM with open weights, designed for tasks like text generation and summarization. It offers high performance, compatibility with TPU hardware, and emphasizes ethical considerations.➽ How Dataplex provides data governance for the AI era? This post introduces Dataplex, a data governance platform that automates discovery, curation, and management of distributed data. It offers features like automated cataloging, lineage tracking, intelligent search, and governance rules, enhancing data quality for generative AI.➽ London Summit: UK businesses turn to Google Cloud AI. This blog highlights Google's AI advancements in the UK, focusing on its new Gemini model's impact across sectors. It covers Google Cloud Summit announcements, partnerships like Vodafone, investments in UK data centers, and support for startups through the new Google Cloud Startup Hub and AI Playground.📊 Success Stories: Real-World ML Case Studies➽ ZODIAC: Bridging LLMs and Cardiological Diagnostics for Enhanced Clinical Precision. This blog discusses the use of LLMs in healthcare, focusing on ZODIAC, an advanced cardiology diagnostic system. It highlights ZODIAC's multi-agent framework, regulatory compliance, and superior performance in clinical settings, surpassing models like GPT-4o and BioGPT.➽ Canvas is a new way to write and code with ChatGPT: This blog introduces Canvas, a new ChatGPT interface for writing and coding projects. Canvas enables collaborative editing, offering feedback, revisions, and shortcuts for tasks like adjusting length or debugging code. It's available to select users during beta.➽ Decision Tree Regressor, Explained: A Visual Guide with Code Examples. This blog introduces Decision Tree Regressors, which predict numerical values using tree structures. It explains their mechanics, construction, and pruning techniques, focusing on post-pruning through cost complexity pruning to prevent overfitting and improve accuracy.➽ 5 AI Projects You Can Build This Weekend (with Python): This blog suggests five AI project ideas for beginners and intermediate developers, emphasizing a problem-first approach. It provides step-by-step guidance and Python libraries for implementing projects like resume optimization, YouTube summarization, and PDF organization.➽ AI Governance with Domino Data Lab on AWS: From Policies to Practices: This blog discusses the importance of AI governance in today's complex regulatory environment, highlighting Domino Data Lab's partnership with AWS. It emphasizes automating AI governance to ensure compliance, mitigate risks, and drive innovation.🌍 ML Newsflash: Latest Industry Buzz & Discoveries➽ 10 GitHub Features That You Are Missing Out On: This blog explores GitHub's advanced features that enhance coding workflows, including GitHub Codespaces for cloud-based development, Copilot for AI coding assistance, Actions for automation, Pages for website hosting, and tools for collaboration, security, and project management.➽ Prompt Caching in LLMs: Intuition. This blog explains how prompt caching reduces computational overhead in AI models by reusing preprocessed prompt segments. It covers the mechanics of caching tokens, embeddings, and internal states, improving efficiency in handling long prompts.➽ Unlock the knowledge in your Slack workspace with Slack connector for Amazon Q Business: This blog introduces Amazon Q Business, an AI-powered assistant that integrates with enterprise applications like Slack. It covers configuring Slack connectors, syncing public and private communications, managing user authentication via AWS IAM, and using retrieval-augmented generation (RAG) for efficient query responses.➽ How Virgin Media O2 simplified internal data sharing with BigQuery Analytics Hub? Virgin Media O2 implemented BigQuery's Analytics Hub to address data-sharing challenges, improving version control, governance, and real-time access. This solution reduced latency, manual effort, and errors, enabling efficient decision-making across teams and saving significant time and resources.We’ve got more great things coming your way—see you soon!*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{line-height:0;font-size:75%} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}}

For a limited time, save on the best-selling books that will elevate your skills and knowledge! @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} } @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} }Transform Your GRC Program. No More Chasing Evidence.If you’re responsible for the GRC program in your organization, don't chase stakeholders for evidence.Use Anecdotes to continuously and indepandantly monitor your tech stack with credible GRC data. Whether you’re complying with SOX, NIST, PCI, or a custom framework, stop managing them in isolation. With Anecdotes’ advanced cross-mapping solution, you can reuse shared evidence across different scopes. 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It covers bio-inspired algorithms like PSO and NEAT, leveraging cloud computing for faster solutions, and applying AI techniques such as NLP and reinforcement learning. It's a great guide for taking your AI projects to the next level with powerful, scalable solutions!➽ Learning Geospatial Analysis with Python - Fourth Edition: This book helps you create powerful GIS solutions using Python 3.10, guiding you through essential geospatial tools like PostGIS, QGIS, and PROJ. It covers automating workflows, handling various data formats, and creating stunning visualizations with Python libraries. You'll also explore remote sensing, real-time data tracking, and geospatial modeling for applications like urban planning and disaster management. 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Verdi by Mercado Libre, Google FRAMES, NotebookLM, Vertex AI Prompt Optimizer, Logic-of-ThoughtIf you are not an AI-powered professional in 2024, you will either:--Get replaced by a person who uses AI--Face a slow career growth & lower salary--Keep spending 10s of hours on tasks that can be done in 10 minutes.But don’t fret– there is one resource that can CHANGE your life, but only if you’re ready to take action NOW.Best thing? It's usually $399, but it's absolutely free for the first 100 readers.Save your seat now (Offer valid for 24 hours only)Register here (first 100 people get it for free + $500 bonus) 🎁SponsoredWelcome to DataPro #114 – Your Weekly Data Science & MLWizardry!🌟Stay ahead in the fast-paced world of AI and ML with the latest insights, strategies, and game-changing tools. This week, we’re bringing you top picks fromtrending data resources to supercharge your projects, boost accuracy, and optimize performance. Ready to level up? Let’s dive in!🔍 Algorithm Spotlight: This Week’s Standout Models✦ MaskLLM: Streamlining LLM Sparsity Training for Big Datasets✦ Prithvi WxC: IBM & NASA’s 2.3B Parameter Model for Weather & Climate✦ LightLLM: High-Speed Python Framework for LLM Inference✦ CopilotKit CoAgents: Simplifying Human-AI Collaboration✦ Blockwise Parallel Decoding (BCD): KAIST & Google’s AI Breakthrough for Faster Language Models🚀 Tech Trends on the Rise✦ Efficient Knowledge Management: How Notion Powers Data Teams✦ Llama 3.2 Locally: Your Quick Start Guide✦ Data Formulator: AI-Powered Visualizations for Analysts✦ RadEdit: Stress-Test Biomedical Vision Models with Synthetic Data✦ OpenAI's Realtime API: Speed Meets Smarts✦ Verdi by Mercado Libre: AI Development Platform Powered by GPT-4o🛠️ Platform Showdown: Must-Try ML Tools & Services✦ Moving Averages with NumPy: Quick How-To✦ Llamafactory Setup: Installation Made Easy✦ ChatGPT for Translation: Bridging Language Gaps in Minnesota✦ Reinforcement Learning: Optimizing Inventory Management with Python✦ AI Agents: Rethinking Autonomy✦ Conversational AI: Solving the Data Democratization Puzzle📊 Real-World Wins: ML Success Stories✦ MALPOLON: AI for Species Distribution Modeling with Deep Learning✦ AMD-135M: AMD's First LLM Series Trained with 670B Tokens✦ MassiveDS: A 1.4 Trillion-Token Datastore for NLP Excellence✦ Vertex AI Prompt Optimizer: Boost Your Generative AI Solutions🌍 ML Newsflash: Industry Breakthroughs & Discoveries✦ Ovis-1.6: Aligning Visual and Textual Embeddings✦ Logic-of-Thought: Enhancing Reasoning in LLMs✦ Instructive Decoding (ID): Boosting Focus in Instruction-Tuned LLMs✦ NotebookLM: Now with Audio & YouTube Integration✦ Google FRAMES: New Dataset for Testing RAG ApplicationsThat’s all for this week’s data-driven insights!Last Chance! For the next 48 hours only, save $150 on your full event pass!BOOK NOW AT $399.99 $239.99Use code LASTCHANCE40 at checkoutImagine being part of 10+ Power Talks, 12+ Hands-On Workshops, and 3 Interactive Roundtables—while networking with 30+ top industry leaders and hundreds of tech professionals from across the globe. This is your opportunity to dive into cutting-edge AI solutions at the Generative AI in Action 2024 Conference.It’s all happening November 11-13 (Virtual)—don’t miss your chance!BOOK YOUR SEAT NOW before prices increase on Saturday!Take our weekly survey and get a free PDF copy of our best-selling book,"Interactive Data Visualization with Python - Second Edition."We appreciate your input and hope you enjoy the book!Share Your Insights and Shine! 🌟💬Cheers,Merlyn Shelley,Editor-in-Chief, Packt.📚 Packt Signature Series: Must-Reads & Author Insights➽ AI-Assisted Programming for Web and Machine Learning: Unlock the power of AI-assisted programming to streamline web development and machine learning. Learn to enhance frontend and backend coding, optimize ML models, and automate tasks using GitHub Copilot and ChatGPT. Perfect for boosting productivity and refining workflows. Start your free trial for access, renewing at $19.99/month.eBook $18.99 $38.99Print + eBook $32.99 $47.99➽ Machine Learning and Generative AI for Marketing: Leverage AI and Python to revolutionize your marketing strategies with predictive analytics and personalized content creation. Learn to combine advanced segmentation techniques and generative AI to boost customer engagement while ensuring ethical AI practices. Perfect for driving real business growth. Start your free trial for access, renewing at $19.99/month.eBook $19.99 $39.99Print + eBook $34.98 $49.99➽ Amazon DynamoDB - The Definitive Guide: Master Amazon DynamoDB with this comprehensive guide, learning key-value data modeling, optimized strategies for transitioning from RDBMS, and efficient read consistency. Discover advanced techniques like caching and analytics integration with AWS services to boost performance, while minimizing latency and costs. Start your free trial for access, renewing at $19.99/month.eBook $17.99 $35.99Print + eBook $30.99 $44.99🔍 Model Breakdown: Unveiling the Algorithm of the Week➽ MaskLLM: A Learnable AI for End-to-End Training of LLM Sparsity on Large Datasets. MaskLLM introduces a learnable pruning method for LLMs using N: M sparsity, reducing computational costs. Through Gumbel Softmax sampling, it enables end-to-end training on large datasets, outperforming existing methods like SparseGPT in perplexity and efficiency.➽ IBM and NASA Release Prithvi WxC: A 2.3B Parameter Foundation Model for Weather and Climate. Prithvi WxC, a 2.3 billion parameter model, uses transformer-based architecture for weather and climate forecasting. It efficiently captures global and local dependencies, outperforming existing models in predicting extreme events and reducing computational costs while generalizing across various forecasting tasks.➽ LightLLM: A Lightweight, Scalable, High-Speed Python Framework for LLM Inference and Serving. LightLLM is an efficient framework designed to deploy large language models (LLMs) in resource-constrained environments like mobile and edge devices. Using techniques such as quantization, pruning, and distillation, it reduces computational demands while maintaining accuracy, enhancing LLM accessibility and usability.➽ CopilotKit’s CoAgents: Simplifying Human Integration with LangGraph Agents. CopilotKit is an open-source framework enabling developers to build AI copilots and in-app agents with real-time context awareness. Its CoAgents beta release supports human-in-the-loop AI, enhancing collaboration between AI and human operators.➽ KAIST and Google AI Introduce Blockwise Parallel Decoding (BCD) to Enhance Efficiency and Fluency in Language Models. This blog discusses Blockwise Parallel Decoding (BPD), a method developed to speed up autoregressive language models by predicting multiple tokens simultaneously, reducing inference latency, and improving efficiency in natural language processing tasks like text generation.🚀 Trendspotting: What's Next in Tech Trends➽ Efficient Knowledge Management for Data Teams Using Notion: This blog explains how data teams can streamline knowledge management using Notion, a platform for productivity and collaboration, to consolidate scattered resources, manage tasks, and enhance team communication across projects efficiently.➽ Using Llama 3.2 Locally: This blog provides a tutorial on using the Msty application to access Llama 3.2 models locally and remotely. It covers downloading, installing, and utilizing lightweight and vision variants for multilingual text generation and image reasoning.➽ Data Formulator: Exploring how AI can help analysts create rich data visualizations: This blog introduces Data Formulator, an open-source tool combining AI and user interface interactions to create rich data visualizations. It enables iterative chart design, using natural language input and data threads for flexible, efficient data visualization.➽ Stress-testing biomedical vision models with RadEdit: A synthetic data approach for robust model deployment: This blog introduces RadEdit, a tool for stress-testing biomedical vision models by simulating dataset shifts using diffusion image editing. It helps researchers identify model weaknesses, ensuring reliable performance across diverse medical conditions and environments.➽ OpenAI’s Realtime API: This blog introduces the Realtime API, enabling developers to build low-latency, speech-to-speech experiences using GPT-4o. It simplifies conversational app development by handling natural voice interactions with a single API call.➽ Building agent + human collaboration with GPT-4o: Dr. Robert Yang founded Altera, a research lab creating "digital humans" capable of interacting and collaborating with people. Using GPT-4, Altera’s AI agents address data degradation, enabling long-term autonomy and emotional intelligence in virtual environments like Minecraft.➽ Mercado Libre Launches Verdi: AI Developer Platform Powered by GPT-4o. This blog introduces Mercado Libre's AI platform, Verdi, which utilizes GPT-4 models to streamline processes like customer service and logistics. Verdi enhances productivity by autonomously handling complex tasks, improving efficiency across Mercado Libre's operations.🛠️ Platform Showdown: Comparing ML Tools & Services➽ How to Compute Moving Averages Using NumPy? This blog explains how to compute various types of moving averages using NumPy, including Simple Moving Average (SMA), Cumulative Moving Average (CMA), and Exponential Moving Average (EMA), commonly used in time-series analysis and financial forecasting.➽ Getting Started with Llamafactory: Installation and Setup Guide. This blog provides a guide on using LlamaFactory, an open-source tool for simplifying LLM training. It supports pretraining, fine-tuning, and RLHF methods, offering an easy setup for various models and training techniques.➽ Minnesota’s Enterprise Translation Office uses ChatGPT to bridge language gaps: Minnesota's Enterprise Translations Office (ETO) uses ChatGPT to provide faster, accurate, and equitable translation services for non-English-speaking residents. By incorporating AI, ETO improves accessibility to public services and addresses cultural relevance.➽ Optimizing Inventory Management with Reinforcement Learning: A Hands-on Python Guide. This blog explains the use of reinforcement learning (RL) for inventory management, specifically using Q-learning. It explores how RL can help optimize ordering policies by learning from data, removing the need for predefined demand models, and balancing inventory costs and demand uncertainty.➽ What Makes a True AI Agent? Rethinking the Pursuit of Autonomy: This blog critiques the hype around AI agents, emphasizing the need for a practical framework to assess agentic behavior. It argues for a spectrum-based approach, highlighting key attributes like perception and interactivity while questioning the true value of fully autonomous AI systems.➽ Why Your Service Engineers Need a Chatbot? This article explains how to build a chatbot using Gemini to assist service engineers with troubleshooting appliances. It highlights challenges with Retrieval-Augmented Generation (RAG) for handling manuals and explores Gemini's advanced features, like context caching and multimodal prompting, integrated into a Streamlit interface.➽ Could Conversational AI-Driven Data Analytics Finally Solve the Data Democratization Riddle? This article explores the potential of conversational AI-driven data analytics, sparked by tools like ChatGPT and Code Interpreter, to democratize data access. However, challenges remain in achieving enterprise-wide solutions for non-technical users.📊 Success Stories: Real-World ML Case Studies➽ MALPOLON: An AI Framework Advancing Species Distribution Modeling with Geospatial Data and Deep Learning. Species distribution modeling (SDM) has evolved from basic statistical methods to advanced machine-learning techniques. The MALPOLON framework, a Python-based deep learning tool, simplifies SDM by integrating multimodal data and improving scalability, accuracy, and accessibility for ecological research.➽ AMD Unveils AMD-135M: Its First Small Language Model Series, Trained on MI250 Accelerators with 670B Tokens. AMD has introduced AMD-135M, a language model with 135 million parameters optimized for its MI250 GPUs. Built on LLaMA2 architecture, it excels in text generation and language comprehension, leveraging datasets like SlimPajama and Project Gutenberg for pretraining.➽ MassiveDS: A 1.4 Trillion-Token Datastore Boosting Efficiency and Accuracy in Knowledge-Intensive NLP Applications. Recent research highlights the benefits of retrieval-based language models (RIC-LMs) that access external datastores during inference. Using the MassiveDS datastore, these models outperform larger parametric models, improving accuracy and efficiency across various tasks.➽ Announcing Vertex AI Prompt Optimizer: Vertex AI Prompt Optimizer simplifies prompt design by automatically optimizing instructions and demonstrations for different models, addressing the challenge of transferring prompts between LLMs. It enhances performance, supports various tasks, and tailors optimization to specific metrics.➽ Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock: Large enterprises face challenges in scaling generative AI while ensuring data privacy, security, compliance, and operational efficiency. This post highlights AWS's guidance, emphasizing Amazon Bedrock's role in securely integrating generative AI, managing risks, and driving innovation across organizations.🌍 ML Newsflash: Latest Industry Buzz & Discoveries➽ Ovis-1.6: An Open-Source MLLM Aligning Visual and Textual Embeddings. Ovis 1.6 is a multimodal large language model that structurally aligns visual and textual embeddings, overcoming traditional alignment challenges. It outperforms competitors in complex multimodal tasks like visual question answering and image captioning.➽ Logic-of-Thought: Boosting Logical Reasoning in Large Language Models with Propositional Logic. Large Language Models (LLMs) struggle with complex reasoning tasks. Logic-of-Thought (LoT) is a new method that enhances LLMs' reasoning by extracting, expanding, and translating logical expressions into natural language, improving performance across multiple reasoning datasets.➽ Instructive Decoding (ID): Enhancing Instruction-Tuned LLMs' Focus on Instructions Without Parameter Updates. Instructive Decoding (ID) enhances instruction-tuned language models by using "noisy instructions" to contrast predictions and improve performance on unseen tasks. This method boosts accuracy without parameter updates, improving generalization and task adherence.➽ NotebookLM Introduces Audio and YouTube Integration, Enhances Audio Overview Sharing: Google's NotebookLM has been enhanced to process audio and YouTube videos, expanding its research capabilities. By transcribing and summarizing multimedia content, it simplifies extracting key points, making research more efficient and comprehensive.➽ Google Releases FRAMES: A Dataset to Test RAG Applications on Factuality, Retrieval Accuracy, and Reasoning. This blog discusses Retrieval-Augmented Generation (RAG), a method combining retrieval mechanisms with generative models to improve factual accuracy and reasoning. It introduces the FRAMES dataset to evaluate RAG's performance in handling complex, multi-document queries.We’ve got more great things coming your way—see you soon!*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{line-height:0;font-size:75%} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}}

GraphReader with Neo4j & LangGraph, Meta’s Llama 3.2, Iteration of Thought, Model2Vec by Minish Lab3 Days. 25+ AI Experts. 30+ Sessions. On November 11, join Vin Vashishta, Denis Rothman, John Thompson, Andreas Welsch, and over 20 AI leaders revolutionizing GenAI across industries. From GenAI tools and AI Agents to Small Language Models and LLM fine-tuning, you’ll dive deep into cutting-edge AI strategies and technologies at Packt's Generative AI In Action conference.Don't delay—secure your spot at the early bird rate before prices increase permanently next week!BOOK NOW AT THE LOWEST PRICE👋 Hello ,Welcome to DataPro #113—Your Weekly Dose of Data Science & ML Wizardry! 🌟In the ever-changing world of AI and ML, staying ahead means having smart strategies for making bold moves. This week, we’ve pulled together fresh insights from our Packt Signature Series and the game-changing data resources from elite tools and repositories. These will help you boost accuracy, optimize performance, and save on costs. So, are you ready to take your data game to the next level? Let’s dive in!📚 Must-Reads for Data Enthusiasts✦ The AI Value Playbook: Unlock AI’s full potential with real-world tips.✦ AI-Assisted Programming: Streamline web and ML development with AI help.✦ ML & Generative AI for Marketing: Revolutionize your marketing strategies.✦ DynamoDB Guide: Your go-to resource for mastering Amazon DynamoDB.Explore these featured articles that are trending now!✦ OpenAI’s MMMLU Dataset: OpenAI's dataset for multilingual LLM evaluation.✦ Vision AI with Llama 3.2: Explore Meta’s latest vision models.✦ Llama-3.1-Nemotron-51B: Pushing the limits of accuracy and efficiency.✦ GenOps: The next frontier of MLOps for Generative AI.✦ Model2Vec by Minish Lab: Lightning-fast sentence transformers.✦ AdvDGMs: Robust adversarial defenses for tabular ML models.✦ RD-Agent by Microsoft: Automate R&D with this open-source AI tool.Enjoy diving into the latest ML magic! Stay sharp, stay curious!Shape the Future of Development and Win Big!Join the Developer Nation Survey! Share how coding has evolved in 2024 and help steer tech innovation. Complete the quick survey for a chance to win amazing prizes like a Samsung Galaxy Watch, Raspberry Pi 5, and more! Plus, your participation supports worthy causes. Don’t miss out!TAKE THE SURVEYSponsoredTake our weekly survey and get a free PDF copy of our best-selling book,"Interactive Data Visualization with Python - Second Edition."We appreciate your input and hope you enjoy the book!Share Your Insights and Shine! 🌟💬Cheers,Merlyn Shelley,Editor-in-Chief, Packt.📚 Packt Signature Series: Must-Reads & Author InsightsWe're thrilled to introduce the latest addition to our Signature Series—a curated collection of the best-selling titles in the data industry! This limited-time offer is packed with expert insights on mastering data science algorithms, Generative AI, and multimodal systems.For a limited time, enjoy50% off eBooksand30% off print editionsof the following must-read titles. But hurry—this offer is only valid untilSeptember 30th!➽ AI-Assisted Programming for Web and Machine Learning: Unlock the power of AI-assisted programming to streamline web development and machine learning. Learn to enhance frontend and backend coding, optimize ML models, and automate tasks using GitHub Copilot and ChatGPT. Perfect for boosting productivity and refining workflows. Start your free trial for access, renewing at $19.99/month.eBook $18.99 $38.99Print + eBook $32.99 $47.99➽ Machine Learning and Generative AI for Marketing: Leverage AI and Python to revolutionize your marketing strategies with predictive analytics and personalized content creation. Learn to combine advanced segmentation techniques and generative AI to boost customer engagement while ensuring ethical AI practices. Perfect for driving real business growth. Start your free trial for access, renewing at $19.99/month.eBook $19.99 $39.99Print + eBook $34.98 $49.99➽ Amazon DynamoDB - The Definitive Guide: Master Amazon DynamoDB with this comprehensive guide, learning key-value data modeling, optimized strategies for transitioning from RDBMS, and efficient read consistency. Discover advanced techniques like caching and analytics integration with AWS services to boost performance, while minimizing latency and costs. Start your free trial for access, renewing at $19.99/month.eBook $17.99 $35.99Print + eBook $30.99 $44.99💡 Expert Insights from the Packt Community 🚀Introducing The AI Value Playbook: How to Make AI Work in the Real WorldBy Lisa Weaver-Lambert, Data and AI Leader in Capital Markets, formerly Microsoft, and AccentureAre you a business leader or board member intrigued by the groundbreaking advances in Generative AI (GenAI) and Large Language Models (LLMs)?If you want to quickly formulate a perspective on how to integrate AI, The AI Value Playbook by Lisa Weaver-Lambert, is a must read. This book addresses the gap in data and AI knowledge in leadership teams that have an appetite for nuanced, targeted and practical solutions. It includes which levers and processes to consider to future-proof businesses. The AI Value Playbook draws on conversations and case studies with leading practitioners across sectors and geographies who share their first-hand experiences successfully driving AI value and pathways for progress.Why is This Book a Must-Read for Business Leaders?Business leaders are challenged by the speed of AI innovation and how to navigate disruption and uncertainty. This book is a crucial resource for those who want to understand how to leverage AI to drive business value, drawn from the firsthand experience of those who have been implementing this technology successfully. In a series of over 30 in-depth and wide-ranging conversations with practitioners, from CEOs leading new generative AI-based companies to Data Scientists and CFOs working in more traditional companies share their hard-earned wisdom. They talk candidly about their successes and failures, and what excites them about the future. These interviews offer unique insights for business leaders to apply to their own organizations. The book distils a value-driven playbook for how AI can be put to work today.Experts include:✦ Sam Liang, CEO of Otter.ai✦ Amr Awadallah, Founder and CEO at Vectara✦ Philipp Heltewig, Co-Founder and CEO at Cognigy✦ Joshua Rubin, Principle AI Scientist at Fiddler AI✦ Zeev Farbman, Co-Founder & CEO at Lightricks…and many more innovators who are actively shaping the AI landscape.Key Topics Covered in the PlaybookThis book provides case studies which explore the specifics of real-world applications. These present detailed analyses of practical scenarios, offering a closer look at the application and impact of AI, such as:✦ How Generative AI Transforms Healthcare Education (LLMs & RAG enabling hyper-personalized learning for healthcare technicians)✦ AI-Powered Virtual Agents Improving Service Efficiency (Real-world examples of AI's impact on customer service operations)✦ Unlocking Profit with AI (Leveraging enterprise data for increased customer profitability and minimizing churn)✦ The Role of Multimodal LLMs in Software Development (Innovations that redefine customer interaction and product creation)The last section of the book is The ‘AI Value Playbook’ a practical framework distilled from the experts and Lisa’s own professional experience, for successful AI implementation. Answers to the Big Questions for Business LeadersThe book tackles the pressing questions business leaders are facing today, such as:✦ How can organizations adapt to the rapid pace of AI innovation?✦ How do we strategically deploy AI to enhance efficiency and drive business value?✦ What risks and ethical considerations should be addressed?✦ How quickly can we start seeing measurable benefits from AI integration?What You’ll Take AwayThe AI Value Playbook distils a value-driven playbook for how AI can be put to work today, including:✦ Fundamentals of AI concepts and the tech stack✦ How AI works with real-world practical applications✦ How to integrate into your company’s overall strategy✦ How to incorporate generative AI in your processes✦ How to drive value with sector-wide examples✦ How to organize an AI-driven operating model✦ How to use AI for competitive advantage✦ The dos and don’ts of AI applicationWith endorsements from Said Business School, University of Oxford, Microsoft leaders, Private Equity and Venture Capital leaders and board leaders, don't miss out on this opportunity to learn from the practical scenarios and strategic plays. The AI Value Playbook is a versatile resource and roadmap to making AI work in the real world—starting today.Get Your Copy Today and Start Driving Real AI Value🔍 Model Breakdown: Unveiling the Algorithm of the Week➽ PromSec: An AI Algorithm for Prompt Optimization for Secure and Functioning Code Generation Using LLM. This blog discusses PromSec, a tool developed to enhance LLM-generated code by optimizing prompts, using gGAN to identify and fix security flaws, ensuring secure, functional, and scalable software development.➽ OpenAI Releases Multilingual Massive Multitask Language Understanding (MMMLU) Dataset on Hugging Face to Easily Evaluate Multilingual LLMs. OpenAI's MMMLU dataset evaluates language models across diverse tasks and languages, promotes fairness for underrepresented languages, enhances problem-solving capabilities, and encourages multilingual, multitask AI model development and research.➽ GraphReader with Neo4j and LangGraph: This blog explains the implementation of the GraphReader agent to retrieve structured information from knowledge graphs. It demonstrates how knowledge graphs are built using Neo4j and LangChain, extracting atomic facts and key elements from documents for enhanced reasoning and retrieval in NLP applications.➽ Vision use cases with Llama 3.2 11B and 90B models from Meta: This blog announces Llama 3.2's availability in Amazon SageMaker and Bedrock, featuring multimodal models supporting text and high-resolution image tasks. Llama 3.2 enhances vision-based reasoning, document question answering, and image captioning.➽ Experimentation to production with Gemini and Vertex AI: This article announces updates to Google Cloud's Gemini and Imagen models, emphasizing increased usage, improved performance, reduced costs, and new capabilities for enterprise AI. Key takeaways include enhanced model control, multimodal support, fine-tuning, and data residency options, all aimed at scaling AI solutions effectively.🚀 Trendspotting: What's Next in Tech Trends➽ Advancing the Accuracy-Efficiency Frontier with Llama-3.1-Nemotron-51B: NVIDIA released the Llama 3.1-Nemotron-51B, an efficient and accurate language model derived from Meta’s Llama-3.1-70B, utilizing Neural Architecture Search (NAS). It offers 2.2x faster inference, reduced memory footprint, and cost-effective deployment on a single NVIDIA H100 GPU. The model provides superior accuracy-efficiency balance, opening new possibilities in AI applications while maintaining strong performance across workloads, revolutionizing efficient AI inference and deployment.➽ Subgroups: An Open-Source Python Library for Efficient and Customizable Subgroup Discovery. The Subgroups Library is an open-source Python tool for Subgroup Discovery (SD), offering efficient, customizable SD algorithms with a scikit-learn interface. It simplifies SD use, supports research, and is widely adopted.➽ Improving Code Quality with Array and DataFrame Type Hints: This article explores the evolution of Python type annotations for complex data structures like arrays and DataFrames. It introduces StaticFrame 2.0, which offers comprehensive type hints, improving both static analysis and runtime validation using NumPy and CallGuard.➽ GenOps: the evolution of MLOps for Gen AI. This article introduces GenOps, the operational framework for scaling Generative AI systems. GenOps extends MLOps by addressing challenges in scaling, compute demands, safety, and unpredictability. Key features include fine-tuning, prompt management, deployment, monitoring, and security for Gen AI models.➽ Llama 3.2 Meta's New generation Models Vertex AI. Meta’s Llama 3.2 models, now available on Vertex AI Model Garden, offer multimodal and lightweight models for edge devices. Key features include image-based reasoning, private AI experiences, easy deployment, and enterprise-level security.🛠️ Platform Showdown: Comparing ML Tools & Services➽ Minish Lab Releases Model2Vec: An AI Tool for Distilling Small, Super-Fast Models from Any Sentence Transformer. Minish Lab's Model2Vec is a groundbreaking tool that distills small, fast models from Sentence Transformers without training data. It enables efficient, scalable NLP tasks on resource-constrained environments with significant performance improvements.➽ AdvDGMs: Enhancing Adversarial Robustness in Tabular Machine Learning by Incorporating Constraint Repair Layers for Realistic and Domain-Specific Attack Generation. This article discusses adversarial machine learning for tabular data, highlighting the introduction of constrained adversarial DGMs (C-AdvDGMs). These models generate realistic adversarial examples by maintaining domain-specific constraints, improving security assessments and model robustness.➽ VoiceChat with Your LLMs using AlwaysReddy: AlwaysReddy is an open-source voice assistant enabling seamless interaction with LLMs via hotkeys. It supports multiple LLM servers, operates locally on various platforms, and ensures privacy, efficiency, and real-time transcription.➽ Introducing customer engagement suite with Google AI: Google Cloud’s Customer Engagement Suite with Google AI integrates conversational AI, omnichannel communication, and Gemini 1.5 multimodal models to enhance customer service. It offers hybrid virtual agents, real-time agent assistance, and AI-driven tools, improving efficiency and customer experience across multiple industries.📊 Success Stories: Real-World ML Case Studies➽ Microsoft Releases RD-Agent: An Open-Source AI Tool Designed to Automate and Optimize Research and Development Processes. Microsoft's RD-Agent automates research and development tasks, enabling faster model evolution, data mining, and hypothesis testing. Its open-source framework enhances efficiency across industries like finance and healthcare, promoting AI-driven innovations.➽ Llama 3.2 Released: Unlocking AI Potential with 1B and 3B Lightweight Text Models and 11B and 90B Vision Models for Edge, Mobile, and Multimodal AI Applications. Meta's Llama 3.2 introduces lightweight (1B and 3B) and multimodal vision models (11B and 90B) for edge devices, enabling efficient AI applications in text and image reasoning. These models support privacy, scalability, and real-time performance.➽ Improve employee productivity using generative AI with Amazon Bedrock: The Employee Productivity GenAI Assistant automates writing tasks using Anthropic’s Claude 3 model on AWS technologies, enhancing creativity and efficiency. It provides customizable templates, supports text/image inputs, and ensures scalability, security, and real-time content generation.➽ Elevate RAG for numerical analysis using Amazon Bedrock Knowledge Bases: Amazon Bedrock Knowledge Bases enhance Retrieval Augmented Generation (RAG) by improving text generation from complex, non-textual data like tables. Features like hybrid search, fixed-size chunking, and comprehensive context retrieval optimize numerical analysis across documents, using managed services like S3 and AWS Lambda for streamlined workflows.🌍 ML Newsflash: Latest Industry Buzz & Discoveries➽ Iteration of Thought: An AI Framework for Enhancing LLM Responses by Generating "thought"-Provoking Prompts. The Iteration of Thought (IoT) framework enhances Large Language Models (LLMs) by iteratively refining reasoning without human feedback. IoT improves accuracy and performance in complex tasks, surpassing traditional prompting methods.➽ Introducing the OpenAI Academy: OpenAI is launching the OpenAI Academy to support developers and mission-driven organizations in low- and middle-income countries. The program offers training, API credits, and community-building to drive AI-driven innovation and economic growth.➽ Build a multimodal social media content generator using Amazon Bedrock: This blog explains how generative AI, using Amazon Bedrock's Claude 3 and Titan models, streamlines social media content creation by automating image and text generation, ensuring brand consistency and rapid production. Key takeaways include efficiency, scalability, and multimodal capabilities.➽ Llama 3.2 models from Meta are now available in Amazon SageMaker JumpStart: The blog announces the availability of Meta's Llama 3.2 multi-modal and lightweight models in Amazon SageMaker JumpStart, enabling efficient AI model deployment and customization. Key features include enhanced performance, responsible innovation, and multi-modal capabilities.We’ve got more great things coming your way—see you soon!*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{line-height:0;font-size:75%} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}}

For a limited time, save on the best-selling books that will elevate your skills and knowledge! @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} }👋 Hello ,✨ Welcome to Packt’s Signature Series: New Titles Just Arrived!📚 We're thrilled to introduce the latest addition to our Signature Series—a curated collection of the best-selling titles in the data industry! This limited-time offer is packed with expert insights on mastering data science algorithms, Generative AI, and multimodal systems.For a limited time, enjoy 50% off eBooks and 30% off print editions of the following must-read titles. But hurry—this offer is only valid until September 30th!Don't miss this opportunity to upskill and elevate your career. Ready to dive in?➽ AI-Assisted Programming for Web and Machine Learning: Unlock the power of AI-assisted programming to streamline web development and machine learning. Learn to enhance frontend and backend coding, optimize ML models, and automate tasks using GitHub Copilot and ChatGPT. Perfect for boosting productivity and refining workflows. Start your free trial for access, renewing at $19.99/month.eBook $18.99 $38.99Print + eBook $32.99 $47.99➽ Machine Learning and Generative AI for Marketing: Leverage AI and Python to revolutionize your marketing strategies with predictive analytics and personalized content creation. Learn to combine advanced segmentation techniques and generative AI to boost customer engagement while ensuring ethical AI practices. Perfect for driving real business growth. Start your free trial for access, renewing at $19.99/month.eBook $19.99 $39.99Print + eBook $34.98 $49.99➽ Amazon DynamoDB - The Definitive Guide: Master Amazon DynamoDB with this comprehensive guide, learning key-value data modeling, optimized strategies for transitioning from RDBMS, and efficient read consistency. Discover advanced techniques like caching and analytics integration with AWS services to boost performance, while minimizing latency and costs. Start your free trial for access, renewing at $19.99/month.eBook $17.99 $35.99Print + eBook $30.99 $44.99➽ Microsoft Power BI Performance Best Practices - Second Edition: Master Power BI performance optimization with this guide, learning to build efficient data models, apply row-level security, and troubleshoot issues using DAX Studio and VertiPaq Analyzer. Implement formal performance management strategies to ensure scalable, high-performing solutions. Start your free trial for access, renewing at $19.99/month.eBook $19.99 $39.99Print + eBook $34.98 $49.99➽ Polars Cookbook: Unlock faster, more efficient data analysis with Python Polars through step-by-step recipes. Master data manipulation, advanced querying, and performance optimization. Learn to handle large datasets, perform complex transformations, and integrate Polars with other tools. Start your free trial for access, renewing at $19.99/month.eBook $17.99 $35.99Print + eBook $30.99 $44.99➽ 15 Math Concepts Every Data Scientist Should Know: Master key data science algorithms through Python-based examples, boosting your solutions by applying and creating algorithms. Learn foundational and advanced mathematical techniques for solving real-world data challenges, with practical Python applications. Start your free trial for access, renewing at $19.99/month.eBook $17.99 $35.99Print + eBook $30.99 $44.99➽ Generative AI-Powered Assistant for Developers: Unlock the full potential of Amazon Q Developer with this comprehensive guide. Learn to auto-generate code across multiple languages, enhance productivity, and streamline workflows with generative AI. Includes real-world examples with AWS integration tips. Start your free trial for access, renewing at $19.99/month.eBook $15.99 $31.99Print + eBook $27.98 $39.99➽ Python Feature Engineering Cookbook - Third Edition: Streamline your machine learning workflows with this comprehensive guide to feature engineering. Learn to craft powerful features from tabular, transactional, and time-series data, develop reproducible pipelines, and optimize transformations to save time. Includes real-world examples for practical application. Start your free trial for access, renewing at $19.99/month.eBook $17.99 $35.99Print + eBook $30.99 $44.99Eager for more insights? Add these powerful resources to your reading list.➽ Bayesian Analysis with Python - Third Edition: Gain hands-on expertise in Bayesian modeling with PyMC, Bambi, and ArviZ. Explore hierarchical models, regression, and BART while applying best practices through practical exercises. Perfect for mastering real-world data science challenges. Includes a free PDF with book purchase.➽ Multiphysics Modeling Using COMSOL 5 and MATLAB: Master COMSOL and MATLAB integration with this comprehensive guide. Learn to set up and solve multiphysics models, from 0D to 3D, through practical examples. Advanced techniques like bioheat and Perfectly Matched Layer models are included, enhancing real-world engineering applications.➽ Python 3 Data Visualization Using ChatGPT / GPT-4: Master Python programming and data visualization with this comprehensive guide. Learn fundamentals and advanced techniques using libraries like Matplotlib and Seaborn. Explore AI integration with ChatGPT/GPT-4 for dynamic visualizations. Companion files with code, datasets, and figures enhance your hands-on learning experience, making this an essential resource for data scientists and Python practitioners.➽ Dealing With Data Pocket Primer: This complete guide covers data science fundamentals, from probability and statistics to advanced NLP and data visualization. Featuring practical examples, clear explanations, and companion files with source code, it’s the perfect resource for mastering data management and analysis efficiently.Here are some more fresh reads, handpicked just for you: ⏩ SQL Pocket Primer⏩ Data Visualization for Business Decisions⏩ Google Gemini for Python⏩ Enterprise Transformation to Artificial Intelligence and the Metaverse⏩ Pandas Basics⏩ Python 3 and Data Visualization⏩ Python 3 Data Visualization Using Google Gemini⏩ Python 3 Using ChatGPT / GPT-4We’ve got more great things coming your way—see you soon!*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{line-height:0;font-size:75%} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}} @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} }

BigQuery’s Contribution Model, Apache Airflow ETL on Google Cloud, Graviton4 EC2 Instances @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} }Join Roman Lavrik from Deloitte Snyk hosted DevSecCon 2024Snyk is thrilled to announce DevSecCon 2024, Developing AI Trust Oct 8-9, a FREE virtual summit designed for DevOps, developer and security pros of all levels. Join Roman Lavrik from Deloitte, among many others, and learn some presciptive DevSecOps methods for AI-powered development.Save your spotSponsoredWelcome to DataPro #112—Your Weekly Fix of Data Science & ML Magic! 🌟In the fast-moving world of AI and ML, staying ahead means leveraging smart strategies for bold decisions. This week, we’re bringing you expert insights from our new Packt Signature Series. From real-time data mastery to AI modeling techniques, we’ve got everything you need to level up your data game!Get ready to elevate your model accuracy, supercharge performance, and cut costs with the latest in scalable solutions. Dive into this week’s must-read articles, tips, and practical techniques.📚 Must-Reads for Data Pros✦ LLM-Powered Apps: Build smarter AI tools✦ Python for Trading: Algorithmic insights✦ Power BI Cookbook: Master data visualization✦ The Prompt Engineering Playbook: Unlock AI secrets✦ Mastering PyTorch: Deep learning unleashed🔍 Algorithm Spotlight: Dive Deep into the Tech✦ Automating Metrics with Amazon Prometheus: Simplify data tracking on EKS✦ Graviton4 EC2 Instances: Memory-optimized power for your AI workloads✦ OpenAI Safety Practices: An update on securing AI✦ Mistral AI Release: Open-source models with unmatched flexibility🚀 Trendspotting: The Future of AI✦ Eureka AI Progress: Understand and evaluate AI advancements✦ OpenAI o1 System Card: A glance into AI innovations✦ Conversational Analytics Preview: What’s new in Looker?✦ Comet’s Opik: Streamlining LLM evaluation and prompt tracking🛠️ Tool Showdown: Which ML Platform Reigns Supreme?✦ BigQuery’s Contribution Model: Fresh insights for your data✦ Running Airflow on Google Cloud: Three easy approaches✦ Python Tricks: Merge dictionaries like a pro✦ Google AI’s DataGemma: A Set of Open Models that Utilize Data Commons📊 Case Studies: ML Success Stories✦ Handling Large Text with Longformer: A Hugging Face deep dive✦ Confluent & Vertex AI: Integrating LLMs for big wins✦ What Makes a Data Business Thrive? Lessons from the top🌍 ML Buzz: Industry News & Discoveries✦ Cracking PyTorch’s Mixed Precision Library: What you need to know✦ MLflow, Azure, Docker: Managing models with ease✦ Self-Learning Models: Teaching AI to improve autonomouslyGet ready for a week of data-driven breakthroughs!Take our weekly survey and get a free PDF copy of our best-selling book,"Interactive Data Visualization with Python - Second Edition."We appreciate your input and hope you enjoy the book!Share Your Insights and Shine! 🌟💬Cheers,Merlyn Shelley,Editor-in-Chief, Packt.Sponsored📚 Packt Signature Series: Must-Reads & Author InsightsWe’re excited to present a new collection in our Signature Series, featuring the best-selling titles in the data industry. Packed with insights on Generative AI and multimodal systems, this collection is available for a limited time at 30% off both print and e-book formats. This offer ends Sunday, September 22nd. Don’t miss your chance to upskill and elevate your career. Let’s dive in!➽ Building LLM Powered Applications: This new titleis all about helping engineers and data pros use large language models (LLMs) effectively. It tackles key challenges like embedding LLMs into real-world apps and mastering prompt engineering techniques. You’ll learn to orchestrate LLMs with LangChain and explore various models, making it easier to create intelligent systems that can handle both structured and unstructured data. It’s a great way to boost your skills, whether you’re new to AI or already experienced! Start your free trial for access, renewing at $19.99/month.eBook $27.98 $39.99Print + eBook $34.98 $49.99➽ Python for Algorithmic Trading Cookbook: This bookis your go-to guide for using Python in trading. It helps you tackle key issues like acquiring and visualizing market data, designing and backtesting trading strategies, and deploying them live with APIs. You’ll learn practical techniques to gather data, analyze it, and optimize your strategies using tools like OpenBB and VectorBT. Whether you’re just starting or looking to refine your skills, this book equips you with the know-how to trade smarter with Python! Start your free trial for access, renewing at $19.99/month.eBook $27.98 $39.99Print + eBook $36.99 $49.99➽ Microsoft Power BI Cookbook - Third Edition: The Power BI Cookbook is your essential guide to mastering data analysis and visualization with Power BI. It covers using Microsoft Data Fabric, managing Hybrid tables, and creating effective scorecards. Learn to transform complex data into clear visuals, implement robust models, and enhance reports with real-time data. This updated edition prepares you for future AI innovations, making it a must-have for beginners and seasoned users alike! Start your free trial for access, renewing at $19.99/month.eBook $29.99 $43.99Print + eBook $41.98 $59.99➽ The Definitive Guide to Power Query (M): The Definitive Guide to Power Query (M) focuses on mastering data transformation with Power Query. It covers fundamental and advanced concepts through hands-on examples that address real-world problems. You'll learn the Power Query M language, optimize performance, handle errors, and implement efficient data processes. By the end, you'll have the skills to enhance your data analysis effectively! Start your free trial for access, renewing at $19.99/month.eBook $43.99Print + eBook $37.99 $54.99🔍 Model Breakdown: Unveiling the Algorithm of the Week➽ Automating metrics collection on Amazon EKS with Amazon Managed Service for Prometheus managed scrapers: This blog discusses how Amazon Managed Service for Prometheus simplifies monitoring containerized applications in Amazon EKS by introducing a fully-managed, agentless scraper for Prometheus metrics, reducing operational overhead and enhancing efficiency through Terraform and AWS CloudFormation automation.➽ Now available: Graviton4-powered memory-optimized Amazon EC2 X8g instances. This post introduces Graviton-4-powered X8g instances, offering high memory, enhanced performance, scalability, and security for applications like databases and electronic design automation, emphasizing their efficiency, flexibility, and improved price-performance over previous instances.➽ An update on OpenAI safety & security practices: This post introduces OpenAI's Safety and Security Committee, outlining five key recommendations to enhance governance, security, transparency, collaboration, and safety frameworks for AI model development and deployment, ensuring responsible and secure advancements in AI technology.➽ Mistral AI Released Mistral-Small-Instruct-2409: A Game-Changing Open-Source Language Model Empowering Versatile AI Applications with Unmatched Efficiency and Accessibility. This article introduces Mistral AI's release of Mistral-Small-Instruct-2409, a powerful open-source large language model designed to enhance AI performance, promote accessibility, and support various natural language processing tasks with an emphasis on transparency, collaboration, and ethical AI development.🚀 Trendspotting: What's Next in Tech Trends➽ Eureka: Evaluating and understanding progress in AI. This post introduces the EUREKA framework for evaluating AI models, emphasizing the need for in-depth measurement beyond standard benchmarks. It aims to uncover strengths, weaknesses, and real-world capabilities of state-of-the-art models through transparent and reproducible evaluations.➽ OpenAI o1 System Card: This report outlines safety evaluations conducted before releasing OpenAI o1 models, addressing risks like bias, hallucinations, and disallowed content. It highlights mitigations, advanced reasoning capabilities, and overall safety ratings under OpenAI's Preparedness Framework.➽ Conversational Analytics in Looker is now in preview: This post introduces Looker's Conversational Analytics, powered by AI and Looker’s semantic model, enabling users to ask data questions in natural language. It simplifies business intelligence, enhances accessibility, and promotes data-driven decision-making across organizations.➽ Comet Launches Opik: A Comprehensive Open-Source Tool for End-to-End LLM Evaluation, Prompt Tracking, and Pre-Deployment Testing with Seamless Integration. This article introduces Opik, an open-source platform by Comet for enhancing observability and evaluation of large language models (LLMs). Opik helps developers and data scientists monitor, test, and track LLM applications, improving performance reliability and addressing issues like hallucinations.🛠️ Platform Showdown: Comparing ML Tools & Services➽ Introducing a new contribution analysis model in BigQuery: This post introduces contribution analysis in BigQuery ML, which helps organizations identify key data drivers behind trends and fluctuations, enabling faster, data-driven decisions by analyzing test and control datasets, and finding statistically significant contributors at scale.➽ Three different ways to run Apache Airflow ETL on Google Cloud: This article explores three ways to run Apache Airflow on Google Cloud, comparing Compute Engine, managed solutions, and infrastructure setups. It highlights the pros and cons of each, providing Terraform code for implementation.➽3 Simple Ways to Merge Python Dictionaries: This blog explains three common methods to merge dictionaries in Python: using the `update()` method, dictionary unpacking (`{**dict1, **dict2}`), and the union operator (`|`), providing code examples for each approach.➽ Google AI Introduces DataGemma: A Set of Open Models that Utilize Data Commons through Retrieval Interleaved Generation (RIG) and Retrieval Augmented Generation (RAG). Google's DataGemma addresses hallucinations in large language models (LLMs) by grounding them in real-world statistical data through Google’s Data Commons. It introduces two advanced models, RAG-27B-IT and RIG-27B-IT, enhancing precision for tasks requiring deep analysis and real-time fact-checking.📊 Success Stories: Real-World ML Case Studies➽ How to Handle Large Text Inputs with Longformer and Hugging Face Transformers? This post is a tutorial on using Longformer with Hugging Face Transformers for processing long text inputs in NLP tasks. It covers installing necessary packages, loading datasets, fine-tuning models, and evaluating results for tasks like review classification.➽ Integrating Confluent and Vertex AI with LLMs: This blog explains how integrating large language models (LLMs) with Confluent and Vertex AI automates SQL query generation, streamlining real-time data analytics. It enhances data exploration, report generation, pipeline optimization, and anomaly detection, addressing challenges like complex queries and real-time decision-making.➽ What Makes a Great Data Business? This post discusses how to identify and evaluate data businesses, highlighting their high margins and value potential. It covers key evaluation criteria: data sources, uses, nice-to-haves, and business models, providing a framework for private equity investors to spot valuable data businesses.🌍 ML Newsflash: Latest Industry Buzz & Discoveries➽ The Mystery Behind the PyTorch Automatic Mixed Precision Library: This article explains how to accelerate deep learning model training using Nvidia's automatic mixed precision (AMP) technique. It introduces Nvidia's Tensor cores, reviews the "Mixed Precision Training" paper, and demonstrates a 2X training speed-up for ResNet50 on FashionMNIST with minimal code changes.➽ Model Management with MLflow, Azure, and Docker: This article explains how to deploy MLflow, a tool for managing machine learning workflows, in a Docker container on Azure for scalability and collaboration. It covers MLflow's key components, focusing on MLflow Tracking, and provides a hands-on guide for setting up the system with Azure SQL Database and Blob Storage.➽ Teaching Your Model to Learn from Itself: This article explains pseudo-labeling, a semi-supervised learning technique that uses confident predictions from a model to label unlabeled data. A case study on the MNIST dataset demonstrates how pseudo-labeling boosted accuracy from 90% to 95% by iteratively adding confident predictions to the training set.We’ve got more great things coming your way—see you soon!*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{line-height:0;font-size:75%} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}} @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} }

For a limited time, save on the best-selling books that will elevate your skills and knowledge! @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} }👋 Hello ,✨ Welcome to Packt’s Signature Series: New Titles Just Arrived!📚 We’re excited to present a new collection in our Signature Series, featuring the best-selling titles in the data industry. Packed with insights on Generative AI and multimodal systems, this collection is available for a limited time at 30% off both print and e-book formats. This offer ends Sunday, September 22nd. Don’t miss your chance to upskill and elevate your career. Let’s dive in!➽ Building LLM Powered Applications: This new titleis all about helping engineers and data pros use large language models (LLMs) effectively. It tackles key challenges like embedding LLMs into real-world apps and mastering prompt engineering techniques. You’ll learn to orchestrate LLMs with LangChain and explore various models, making it easier to create intelligent systems that can handle both structured and unstructured data. It’s a great way to boost your skills, whether you’re new to AI or already experienced! Start your free trial for access, renewing at $19.99/month.eBook $27.98 $39.99Print + eBook $34.98 $49.99➽ Python for Algorithmic Trading Cookbook: This bookis your go-to guide for using Python in trading. It helps you tackle key issues like acquiring and visualizing market data, designing and backtesting trading strategies, and deploying them live with APIs. You’ll learn practical techniques to gather data, analyze it, and optimize your strategies using tools like OpenBB and VectorBT. Whether you’re just starting or looking to refine your skills, this book equips you with the know-how to trade smarter with Python! Start your free trial for access, renewing at $19.99/month.eBook $27.98 $39.99Print + eBook $36.99 $49.99➽ Microsoft Power BI Cookbook - Third Edition: The Power BI Cookbook is your essential guide to mastering data analysis and visualization with Power BI. It covers using Microsoft Data Fabric, managing Hybrid tables, and creating effective scorecards. Learn to transform complex data into clear visuals, implement robust models, and enhance reports with real-time data. This updated edition prepares you for future AI innovations, making it a must-have for beginners and seasoned users alike! Start your free trial for access, renewing at $19.99/month.eBook $29.99 $43.99Print + eBook $41.98 $59.99➽ The Definitive Guide to Power Query (M): The Definitive Guide to Power Query (M) focuses on mastering data transformation with Power Query. It covers fundamental and advanced concepts through hands-on examples that address real-world problems. You'll learn the Power Query M language, optimize performance, handle errors, and implement efficient data processes. By the end, you'll have the skills to enhance your data analysis effectively! Start your free trial for access, renewing at $19.99/month.eBook $43.99Print + eBook $37.99 $54.99➽ Mastering PyTorch - Second Edition: This is your essential resource for building advanced neural network models with PyTorch. You'll explore tools like Hugging Face, fastai, and Docker, learning to create models for text, images, and music. With hands-on examples, you'll master training optimization, mobile deployment, and various network types, equipping you to tackle complex AI tasks using the PyTorch ecosystem! Start your free trial for access, renewing at $19.99/month.eBook $28.99 $41.99Print + eBook $40.99 $51.99➽ Unlocking the Secrets of Prompt Engineering: It'syour guide to mastering AI-driven writing with large language models (LLMs). It covers essential techniques and applications, from content creation to chatbots. With practical examples, you'll learn to generate product descriptions and tackle advanced uses like podcast creation. The book emphasizes ethical practices and optimization strategies, preparing you to leverage AI for improved writing, creativity, and productivity! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $30.99 $44.99➽ ChatGPT for Cybersecurity Cookbook: Your essential guide to using AI in cybersecurity. It helps you automate tasks like penetration testing, risk assessment, and threat detection with ChatGPT. Each recipe provides step-by-step instructions for generating commands, writing code, and creating tools with the OpenAI API and Python. You'll explore innovative strategies and optimize workflows, gaining confidence in AI-driven techniques to excel in the rapidly evolving cybersecurity landscape! Start your free trial for access, renewing at $19.99/month.eBook $27.98 $39.99Print + eBook $34.98 $49.99➽ Mastering NLP from Foundations to LLMs:Your complete guide to Natural Language Processing (NLP) with Python. It covers the mathematical foundations of machine learning and essential topics like linear algebra and statistics. You'll learn to preprocess text, classify it, and implement advanced techniques, including large language models (LLMs). With practical Python code samples and insights into future trends, you'll gain the skills to tackle real-world NLP challenges confidently and effectively design ML-NLP systems! Start your free trial for access, renewing at $19.99/month.eBook $29.99 $42.99Print + eBook $46.99 $52.99➽ Learn Microsoft Fabric: This title is your essential guide to using Microsoft Fabric for data integration and analytics. It explores key features with real-world examples, helping you build solutions for lakehouses, data warehouses, and real-time analytics. You'll learn to effectively monitor your Fabric platform and cover workloads like Data Factory and Power BI. By the end, you'll be equipped to unlock AI-driven insights and navigate the analytics landscape confidently! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $35.98 $44.99➽ Building Data-Driven Applications with LlamaIndex: This book is your comprehensive guide to leveraging Generative AI and large language models (LLMs). It addresses challenges like memory constraints and data gaps while teaching you to build interactive applications with LlamaIndex. You'll learn to ingest and index data, create optimized indexes, and query your knowledge base through hands-on projects. By the end, you'll be equipped to troubleshoot LLM issues and confidently deploy your AI-driven applications! Start your free trial for access, renewing at $19.99/month.eBook $24.99 $35.99Print + eBook $30.99 $44.99➽ OpenAI API Cookbook: This new title is all about using the OpenAI API to create smart applications. It helps engineers and data pros understand the basics, set up their API, and build tailored tools like chatbots and virtual assistants. You’ll learn practical recipes to enhance user experience and integrate AI into your workflows, making your projects more efficient and innovative! Start your free trial for access, renewing at $19.99/month.eBook $21.99 $31.99Print + eBook $27.98 $39.99Loved Those Titles? Check These Out!➽ Data Governance Handbook➽ Generative AI for Cloud Solutions➽ Data-Centric Machine Learning with Python➽ Modern Python Cookbook - Third EditionWe’ve got more great things coming your way—see you soon!*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{line-height:0;font-size:75%} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}} @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} }

Google’s AI detective, Regnology Automates Ticket-to-Code with agentic GenAI on Vertex AI, MedFuzz @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} }Grow your business & career by 10x using AI Strategies in 4 hrs! 🤯Join GrowthSchool's AI Business Growth & Strategy Crash Course and discover how to revolutionise your approach to business on 12th September at 10 AM EST.In just 4 hours, you’ll gain the tools, insights, and strategies to not just survive, but dominate your market.This is more than just a workshop—it's a turning point.The first 100 to register get in for FREE. Don’t miss the chance to change your business trajectory forever.Sign up here to save your seat! 👈SponsoredWelcome to DataPro #111—Your Weekly Dose of Data Science & ML Magic! 🚀We’re now landing in your inbox every Thursday to keep you sharp and ahead of the game!In the ever-evolving realm of AI and ML, it's all about harnessing smart insights for impactful decisions and stellar leadership. Dive into our new Packt Signature Series, where you'll find expert tips on everything from real-time data management to mastering AI modeling. We’re here to equip you with the tools you need to navigate the data world like a pro.This week, we’ve got cutting-edge strategies to boost your model accuracy, optimize performance, and reduce costs with scalable solutions. Get ready for top-notch tips and practical techniques to supercharge your data skills.📚 Top Reads & Author Insights:✦ Building AI Intensive Python Applications:Dive deep into advanced AI apps.✦ Databricks ML in Action: Real-world applications and best practices.✦ Generative AI Application Integration Patterns:Innovative uses of generative AI.✦ Polars Cookbook:Essential recipes for efficient data handling.✦ Building LLM Powered Applications:Building with large language models.✦ Building Data-Driven Applications with LlamaIndex:Leveraging LlamaIndex for robust applications.✦ Data Quality in the Age of AI:Ensuring top-notch data quality.✦ Modern Computer Vision with PyTorch - Second Edition:Updated techniques in computer vision.✦ Accelerate Model Training with PyTorch 2.X:Speed up your model training.✦ Mastering PyTorch - Second Edition:The ultimate guide to mastering PyTorch.🔍 Algorithm Spotlight:✦ Apple’s Byte-Level ASR Optimization: A new AI algorithm for speech recognition.✦ IBM’s PowerLM-3B & PowerMoE-3B: Massive language models with advanced scheduling.✦ AtScale’s Open-Sourced SML: Transforming analytics with a new semantic modeling framework.✦ LG’s EXAONEPath: Enhancing histopathology analysis with a pre-trained model.🚀 Tech Trendwatch:✦ Tracing Memory Allocation in Python: Learn how to track memory usage.✦ Anomaly Detection in Streaming Data: Using Amazon Managed Service for Apache Flink.🛠️ ML Tool Showdown:✦7 Free Cloud IDEs You Need: Explore top IDEs for data science.✦ End-to-End Data Science Pipelines: From ingestion to visualization.✦ Sustainable MLOps: Optimizing operations for sustainability.📊 Success Stories:✦ GraphRAG’s Auto-Tuning: Adapting rapidly to new domains.✦ Enterprise Data Quality Guide: Navigating enterprise data challenges.✦ AI Agents for Daily Tasks: Automating routine app tasks.🌍 ML Newsflash:✦ Google’s AI Detective: Solving challenges with Gemini 1.5 Pro.✦ Regnology’s Gen AI on Vertex AI: Automating ticket-to-code processes.✦ MedFuzz on LLM Robustness: Evaluating LLMs in medical contexts.Stay tuned for your weekly dose of data brilliance! 🚀Take our weekly survey and get a free PDF copy of our best-selling book, "Interactive Data Visualization with Python - Second Edition."We appreciate your input and hope you enjoy the book!Share Your Insights and Shine! 🌟💬📚 Packt Signature Series: Must-Reads & Author InsightsStep into a world of expert-driven knowledge with ourone-of-a-kindin-house content, crafted by industry pros to deliver the freshest insights on the latest tech releases. Discover how these cutting-edge titles are shaping the data landscape and unlocking the "whats," "hows," and "whys" behind emerging technologies. Whether you're looking to sharpen your skills or dive into something entirely new, there's never been a better time to expand your library with these essential resources.For a limited time, enjoy 30% off all eBooks at Packtpub.com. These books are more than just guides, they’re packed with real-world expertise from those who know the industry inside and out, offering perspectives you simply won’t find anywhere else.➽ Building AI Intensive Python ApplicationsThis book guides you through building powerful AI applications using large language models (LLMs), vector databases, and Python frameworks. You'll learn how to optimize AI performance, implement advanced techniques like retrieval-augmented generation, and tackle challenges like hallucinations and data leakage, ultimately creating reliable, high-impact AI solutions.Order Today at $41.98 $59.99➽ Databricks ML in ActionThis book is all about mastering the Databricks platform for machine learning and data science. It helps data engineers and scientists solve key problems by offering practical, cloud-agnostic examples and code projects. You’ll learn how to use Databricks tools to streamline workflows, improve model performance, and integrate with third-party apps.Order Today at $24.99 $35.99➽ Generative AI Application Integration PatternsThis book guides you through designing and integrating GenAI applications. You’ll learn essential tools and strategies, from prompt engineering to advanced techniques like retrieval-augmented generation. It provides practical examples, a clear 4-step framework, and covers ethical considerations for deploying GenAI models effectively.Order Today at $27.98 $39.99➽ Polars CookbookThis cookbook is your go-to guide for mastering Python Polars, a high-performance library for efficient data analysis. It offers step-by-step recipes for handling large datasets, advanced querying, and performance optimization. With practical tips on data manipulation, integration, and deployment, you'll boost your data workflows and analysis skills.Order Today at $24.99 $35.99➽ Building LLM Powered ApplicationsThis book helps you integrate LLMs into real-world apps using LangChain for orchestration. It covers the basics and advanced techniques of prompt engineering, explores various LLM architectures, and guides you through using powerful tools to create intelligent agents. You'll also learn about ethical considerations and the future of large foundation models.Order Today at $27.98 $39.99➽ Building Data-Driven Applications with LlamaIndexThis guide explores Generative AI and LlamaIndex, focusing on overcoming LLM limitations and building interactive applications. Learn to manage text chunking, security, and real-time data challenges. With hands-on projects, you'll master data ingestion, indexing, querying, and deployment, equipping you to develop and customize sophisticated AI-driven solutions.Order Today at $24.99 $35.99➽ Data Quality in the Age of AIThis book emphasizes the crucial role of data quality in AI success. It provides strategies to improve and measure data quality, offering practical steps to enhance data-driven decision-making. With real-world examples and actionable insights, it equips teams to optimize their data culture, leading to better AI performance and business outcomes.Order Today at $55.98 $79.99➽ Modern Computer Vision with PyTorch - Second EditionThis book offers a deep dive into neural network architectures and PyTorch for computer vision tasks. Learn to build solutions for image classification, object detection, and more using state-of-the-art models like CLIP and Stable Diffusion. With code available on GitHub and Google Colab, you'll gain practical skills for real-world applications and production deployment.Order Today at $33.99 $48.99➽ Accelerate Model Training with PyTorch 2.XThis book helps you optimize PyTorch model training, focusing on reducing build time and improving efficiency. Learn to speed up training with multicore systems, multi-GPU setups, and mixed precision. You'll explore techniques for model simplification, specialized libraries, and data pipeline improvements to enhance performance and model quality.Order Today at $24.99 $35.99➽ Mastering PyTorch - Second Edition This book guides you through building advanced neural network models with PyTorch, including CNNs, RNNs, and transformers. Learn to optimize training with GPUs, deploy models on mobile, and utilize libraries like Hugging Face and PyTorch Lightning. It covers deep learning across text, vision, and music, enhancing your AI skills with practical techniques.Order Today at $28.99 $41.99🔍 Model Breakdown: Unveiling the Algorithm of the Week➽ Apple Researchers Propose a Novel AI Algorithm to Optimize a Byte-Level Representation for Automatic Speech Recognition ASR and Compare it with UTF-8 Representation: The blog discusses a new method for enhancing multilingual automatic speech recognition (ASR) using vector quantized auto-encoders. This approach improves byte-level representation accuracy, optimizes resource usage, and reduces error rates, outperforming UTF-8 and character-based methods in multilingual settings.➽ PowerLM-3B and PowerMoE-3B Released by IBM: Revolutionizing Language Models with 3 Billion Parameters and Advanced Power Scheduler for Efficient Large-Scale AI Training. IBM's PowerLM-3B and PowerMoE-3B models showcase advancements in large-scale language model training. Utilizing IBM’s Power scheduler, these models achieve high efficiency and scalability, optimizing learning rates and computational costs for improved performance in NLP tasks.➽ AtScale Open-Sourced Semantic Modeling Language (SML): Transforming Analytics with Industry-Standard Framework for Interoperability, Reusability, and Multidimensional Data Modeling Across Platforms: AtScale has open-sourced its Semantic Modeling Language (SML) to create a standardized, interoperable language for semantic modeling across platforms. Built on YAML, SML supports complex data structures, promotes reusability, and integrates with modern development practices, aiming to enhance collaboration and efficiency in analytics.➽ LG AI Research Open-Sources EXAONEPath: Transforming Histopathology Image Analysis with a 285M Patch-level Pre-Trained Model for Variety of Medical Prediction, Reducing Genetic Testing Time and Costs: LG AI Research's EXAONEPath enhances digital histopathology by addressing Whole Slide Image (WSI) challenges with advanced self-supervised learning and stain normalization. This open-source model improves diagnostic accuracy, reduces genetic testing time, and supports various medical tasks.🚀 Trendspotting: What's Next in Tech Trends➽ How to Trace Memory Allocation in Python? This tutorial demonstrates how to use Python's `tracemalloc` module for tracing memory allocation in memory-intensive operations. It covers setting up a sample dataset, tracking memory usage before and after processing, and comparing snapshots to debug memory issues.➽ Anomaly detection in streaming time series data with online learning using Amazon Managed Service for Apache Flink: This post describes building a real-time anomaly detection system for time series data using AWS services. It outlines how to deploy an end-to-end solution with Amazon Managed Service for Apache Flink, Kafka, and SageMaker, focusing on detecting unusual patterns in streaming data.🛠️ Platform Showdown: Comparing ML Tools & Services➽ 7 Free Cloud IDE for Data Science That You Are Missing Out: To start data science projects quickly, explore these 7 Cloud IDEs: Kaggle Notebooks, Deepnote, Lightning.ai, Datalab by DataCamp, Google Colab, Amazon SageMaker Studio Lab, and DataLore. Each provides pre-built environments and free access to GPUs.➽ Developing End-to-End Data Science Pipelines with Data Ingestion, Processing, and Visualization: The article discusses the iterative nature of data science projects, emphasizing the importance of data ingestion, processing, and visualization. It outlines an end-to-end process involving business understanding, data preparation, model building, and monitoring.➽ Optimizing MLOps for Sustainability: The post outlines optimizing MLOps for sustainability using AWS by improving data preparation, model training, and deployment. Key practices include selecting low-carbon impact regions, using efficient storage, leveraging SageMaker’s tools, and monitoring with AWS services to minimize resource use and emissions.📊 Success Stories: Real-World ML Case Studies➽ GraphRAG auto-tuning provides rapid adaptation to new domains: Microsoft Research's GraphRAG uses large language models to build domain-specific knowledge graphs from text, enabling complex query responses. The tool automates the creation of domain-specific prompts to enhance graph accuracy and streamline knowledge extraction.➽ The “Who Does What” Guide to Enterprise Data Quality: This analysis explores enterprise data quality management, focusing on roles and processes in data detection, triage, resolution, and measurement. It highlights the importance of foundational versus derived data products, and strategies for improving data quality and efficiency.➽ Can AI Agents Do Your Day-to-Day Tasks on Apps? The blog introduces AppWorld, a new benchmarking framework for AI agents that interact with various apps to perform complex tasks. It features a simulated environment, a benchmark of intricate tasks, and a robust evaluation framework to test and improve AI agents’ performance.🌍 ML Newsflash: Latest Industry Buzz & Discoveries➽ Google’s AI detective: The Needle in a Haystack test and how Gemini 1.5 Pro solves it. The blog discusses Google's Gemini 1.5 Pro, an AI model excelling in the "Needle in a Haystack" test. It showcases the model's ability to retrieve specific information from vast datasets across text, video, and audio, outperforming GPT-4 in complex retrieval tasks.➽ Regnology Automates Ticket-to-Code with GenAI on Vertex AI: The blog discusses Regnology's solution to the "Ticket-to-Code Problem," where bug reports are transformed into actionable code. Their Ticket-to-Code Writer tool, enhanced by Google’s Vertex AI and Gemini 1.5 Pro, automates this process, boosting efficiency by 60% and improving accuracy.➽ MedFuzz: Exploring the robustness of LLMs on medical challenge problems. LLMs excel in medical benchmarks but often oversimplify complex real-world scenarios. MedFuzz, inspired by security red-teaming and fuzzing, introduces adversarial challenges to test LLMs against these simplifying assumptions. This approach assesses their true effectiveness in nuanced clinical settings.*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{line-height:0;font-size:75%} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}} @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} }

Discover fresh perspectives and actionable solutions in our Signature Series. @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} }🔥 30% Off All eBooks! Level Up Your Data Skills with Signature Series InsightsLive Webinar: The Power of Data Storytelling in Driving Business Decisions (September 10, 2024 at 9 AM CST)Data doesn’t have to be overwhelming. Join our webinar to learn about Data Storytelling and turn complex information into actionable insights for faster decision-making.Click below to check the schedule in your time zone and secure your spot. Can't make it? Register to get the recording instead.REGISTER FOR FREESponsored✨ Welcome to Packt’s Signature Series: New Titles Just Arrived!📚 Introducing our latest special edition: the Signature Series! This exclusive collection delivers fresh perspectives, practical insights, and solutions designed to address today’s key data challenges."Data is the new oil, but refining it is the real challenge." – UnknownIn a field where rapid change and increasing complexity are the norms, staying ahead requires more than basic knowledge. At Packt, we’re committed to providing you with the latest insights and actionable solutions from top experts in the industry.Why You Should Explore This Signature Series:🔍 Tackle Today’s Challenges: Our new releases focus on critical issues, from managing real-time data to mastering predictive analytics, giving you the tools to navigate the data landscape effectively.🚀 Lead the Way: These books feature innovative strategies and practical applications, ensuring you’re not just keeping up but leading in the data domain.🎁 Direct Buying Perks at PacktPub: Enjoy a 30% discount on all eBooks and a 7-day free trial of our subscription service. This is your opportunity to access cutting-edge knowledge and stay ahead of the curve.Explore the Latest Titles in Our Signature Series:➽"Data Science for Decision Makers": Transform your leadership with cutting-edge data science and AI insights by Jon Howells.➽"Data Science for IoT Engineers": Discover how to apply data science and machine learning to drive innovation in IoT with P. G. Madhavan.➽"Bash for Data Scientists": Master shell scripting for your data science projects with expert guidance from Oswald Campesato.➽"Angular and Machine Learning Pocket Primer": Get up to speed on merging machine learning with Angular with this handy guide by Oswald Campesato.➽"AI, ML, and Deep Learning": Dive into advanced AI techniques and practical deep learning methods with Oswald Campesato’s expert advice.Don’t miss this opportunity to enhance your data expertise with insights from industry leaders. Dive into the Signature Series and elevate your skills today!💥Transform Your Data Game with This Week’s Must-Reads“In the world of data, knowledge is power. And the right book can turn complexity into clarity.”This week, we’re excited to present new releases that cater to the evolving needs of data professionals. Whether you're aiming to enhance your data strategy, unravel complex analytics, or adopt the latest technologies, these expertly crafted titles are your gateway to advanced skills and insights.These resources are designed to help you tackle real-world data challenges and advance your skills.Check out our new titles and see how they can support your data journey. Let’s keep learning and growing together!Order Today at $24.99 $35.99Data Science for Decision Makers: Enhance your leadership skills with data science and AI expertiseBy Jon HowellsStruggling to bridge the gap between data science and business leadership? Our new book is here to help!What you’ll gain:✔️ Master statistics and ML to interpret models and drive decisions.✔️ Identify AI opportunities and oversee data projects from start to finish.✔️ Empower teams to tackle complex problems and build AI solutions.Elevate your leadership and make data work for you! Get the book now—just $24.99, down from $35.99!Order Today at $34.98$49.99Data Science for IoT Engineers: Master Data Science Techniques and Machine Learning Applications for Innovative IoT SolutionsBy Mercury Learning and Information, P. G. MadhavanDive into our new book, crafted for engineers, physicists, and mathematicians eager to bridge the gap between theory and practice!What’s inside:✔️ Integrate systems theory and machine learning seamlessly.✔️ Apply practical solutions like digital twins to real-world problems.✔️ Progress from basics to advanced techniques with ease.Whether you're tackling IoT challenges or modeling complex systems, this workbook with MATLAB code will guide you every step of the way. Get the eBook now for just $34.98, down from $49.99! Elevate your skills and tackle IoT and complex systems with confidence.Order Today at $37.99$54.99Bash for Data Scientists: A Comprehensive Guide to Shell Scripting for Data Science TasksBy Mercury Learning and Information, Oswald CampesatoUnlock the power of Bash for your data science projects with our latest book!What’s inside:✔️ Master Bash for efficient data processing with practical, real-world examples.✔️ Learn to integrate with Pandas and databases for advanced data handling.✔️ Get hands-on with grep, sed, and awk to clean and manage datasets effectively.Grab the eBook now for just $37.99, originally $54.99! Elevate your scripting skills and streamline your data tasks today!Order Today at $27.98$39.99Angular and Machine Learning Pocket Primer: A Comprehensive Guide to Angular and Integrating Machine LearningBy Mercury Learning and Information, Oswald CampesatoReady to elevate your Angular apps with machine learning? 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Transform your understanding and apply these cutting-edge concepts in real-world scenarios.We’ve got more great things coming your way—see you soon!*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{line-height:0;font-size:75%} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}} @media only screen and (max-width: 100%;} #pad-desktop {display: none !important;} }