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The Definitive Guide to Google Vertex AI

You're reading from  The Definitive Guide to Google Vertex AI

Product type Book
Published in Dec 2023
Publisher Packt
ISBN-13 9781801815260
Pages 422 pages
Edition 1st Edition
Languages
Concepts
Authors (2):
Jasmeet Bhatia Jasmeet Bhatia
Profile icon Jasmeet Bhatia
LinkedIn
Jasmeet is a Machine Learning Architect with over 8 years of experience in Data Science and Machine Learning Engineering at Google and Microsoft, and overall has 17 years of experience in Product Engineering and Technology consulting at Deloitte, Disney, and Motorola. He has been involved in building technology solutions that focus on solving complex business problems by utilizing information and data assets. He has built high performing engineering teams, designed and built global scale AI/Machine Learning, Data Science, and Advanced analytics solutions for image recognition, natural language processing, sentiment analysis, and personalization.
See other products by Jasmeet Bhatia
Kartik Chaudhary Kartik Chaudhary
Profile icon Kartik Chaudhary
LinkedIn
​Kartik is an Artificial Intelligence and Machine Learning professional with 6+ years of industry experience in developing and architecting large scale AI/ML solutions using the technological advancements in the field of Machine Learning, Deep Learning, Computer Vision and Natural Language Processing. Kartik has filed 9 patents at the intersection of Machine Learning, Healthcare, and Operations. Kartik loves sharing knowledge, blogging, travel, and photography.
See other products by Kartik Chaudhary
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Table of Contents (24) Chapters

Preface Part 1:The Importance of MLOps in a Real-World ML Deployment
Chapter 1: Machine Learning Project Life Cycle and Challenges Chapter 2: What Is MLOps, and Why Is It So Important for Every ML Team? Part 2: Machine Learning Tools for Custom Models on Google Cloud
Chapter 3: It’s All About Data – Options to Store and Transform ML Datasets Chapter 4: Vertex AI Workbench – a One-Stop Tool for AI/ML Development Needs Chapter 5: No-Code Options for Building ML Models Chapter 6: Low-Code Options for Building ML Models Chapter 7: Training Fully Custom ML Models with Vertex AI Chapter 8: ML Model Explainability Chapter 9: Model Optimizations – Hyperparameter Tuning and NAS Chapter 10: Vertex AI Deployment and Automation Tools – Orchestration through Managed Kubeflow Pipelines Chapter 11: MLOps Governance with Vertex AI Part 3: Prebuilt/Turnkey ML Solutions Available in GCP
Chapter 12: Vertex AI – Generative AI Tools Chapter 13: Document AI – An End-to-End Solution for Processing Documents Chapter 14: ML APIs for Vision, NLP, and Speech Part 4: Building Real-World ML Solutions with Google Cloud
Chapter 15: Recommender Systems – Predict What Movies a User Would Like to Watch Chapter 16: Vision-Based Defect Detection System – Machines Can See Now! Chapter 17: Natural Language Models – Detecting Fake News Articles! Index Other Books You May Enjoy

Vision AI on Google Cloud

Computer vision is a field of artificial intelligence (AI) that enables computers and systems to derive insights from visual data such as digital images and videos. Understanding images and videos is a complex task, but with never-ending research in the field, the AI research community has led to the development of many smart ways of getting information out of unstructured data, such as images and videos. Information extracted from digital images and videos can be leveraged by businesses to take action and provide recommendations at scale. Google Cloud provides the following two offerings as a platform to solve computer vision problems:

  • Vision AI
  • Video AI

Now, let’s deep dive into each of these offerings.

Vision AI

Google Vision AI provides a platform for creating vision-based applications with pre-trained APIs, AutoML, or custom models. Using Vision AI, we can create image and video analytics solutions in just a few minutes...

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Authors (2)

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Profile icon Jasmeet Bhatia
LinkedIn
Jasmeet is a Machine Learning Architect with over 8 years of experience in Data Science and Machine Learning Engineering at Google and Microsoft, and overall has 17 years of experience in Product Engineering and Technology consulting at Deloitte, Disney, and Motorola. He has been involved in building technology solutions that focus on solving complex business problems by utilizing information and data assets. He has built high performing engineering teams, designed and built global scale AI/Machine Learning, Data Science, and Advanced analytics solutions for image recognition, natural language processing, sentiment analysis, and personalization.
Read more
See other products by Jasmeet Bhatia
Profile icon Kartik Chaudhary
LinkedIn
​Kartik is an Artificial Intelligence and Machine Learning professional with 6+ years of industry experience in developing and architecting large scale AI/ML solutions using the technological advancements in the field of Machine Learning, Deep Learning, Computer Vision and Natural Language Processing. Kartik has filed 9 patents at the intersection of Machine Learning, Healthcare, and Operations. Kartik loves sharing knowledge, blogging, travel, and photography.
See other products by Kartik Chaudhary
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