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AI Enhancement with Knowledge Graphs - Mastering RAG Systems
AI Enhancement with Knowledge Graphs - Mastering RAG Systems

AI Enhancement with Knowledge Graphs - Mastering RAG Systems: Unleashing the Power of Knowledge Graphs in RAG Systems

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Profile Icon Paulo Dichone
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$89.99
Video Sep 2024 2hrs 36mins 1st Edition
Video
$89.99
Subscription
Free Trial
Renews at $19.99p/m
Arrow left icon
Profile Icon Paulo Dichone
Arrow right icon
$89.99
Video Sep 2024 2hrs 36mins 1st Edition
Video
$89.99
Subscription
Free Trial
Renews at $19.99p/m
Video
$89.99
Subscription
Free Trial
Renews at $19.99p/m

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Key benefits

  • In-depth knowledge graph training to master their structure and use in AI applications
  • Hands-on Neo4j experience to build, manage, and query complex knowledge graphs effectively
  • Advanced RAG integration techniques to enhance AI models with vector indexing and data retrieval

Description

Unlock the potential of knowledge graphs and RAG systems in this comprehensive course. Begin by setting up your development environment and configuring tools like the OpenAI API. You'll explore fundamental concepts of knowledge graphs, their structure, and their critical role in data systems. These early modules provide a strong foundation, ensuring you're ready for hands-on applications and more advanced topics. Moving forward, you’ll dive into practical implementation using Neo4j, a popular graph database. You’ll learn to construct and manage knowledge graphs, create entities and relationships, and execute complex queries to extract meaningful insights. Each lesson is designed to build your skills step-by-step, offering real-world scenarios to deepen your understanding. By the end of this section, you’ll be equipped to handle knowledge graphs effectively in diverse projects. The course then focuses on integrating knowledge graphs with RAG systems to enhance AI applications. You’ll master techniques such as vector indexing and embedding creation for efficient data retrieval. The final project brings everything together, enabling you to build a complete GraphRAG system. This course offers a thorough journey into a cutting-edge area of AI and data science, equipping you with the expertise to innovate and lead in your field.

Who is this book for?

This course is ideal for data scientists, AI developers, and technical professionals who are familiar with Python and have basic knowledge of machine learning concepts. Prior experience with databases and APIs is recommended but not required.

What you will learn

  • Build and manage comprehensive knowledge graphs using Neo4j
  • Configure development environments and integrate AI tools effectively
  • Query and analyze complex data sets with graph databases
  • Implement RAG systems to improve AI data retrieval and performance
  • Develop advanced vector indexing and embedding techniques
  • Apply knowledge graph skills to real-world AI applications and projects

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Sep 30, 2024
Length: 2hrs 36mins
Edition : 1st
Language : English
ISBN-13 : 9781836645252
Category :
Languages :

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Product Details

Publication date : Sep 30, 2024
Length: 2hrs 36mins
Edition : 1st
Language : English
ISBN-13 : 9781836645252
Category :
Languages :

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Table of Contents

8 Chapters
Introduction Chevron down icon Chevron up icon
Development Environment Setup Chevron down icon Chevron up icon
Knowledge Graph Deep Dive Chevron down icon Chevron up icon
Hands-On: Knowledge Graph Deep Dive - Neo4j Introduction and Overview Chevron down icon Chevron up icon
Knowledge Graphs & RAG Systems Chevron down icon Chevron up icon
Knowledge Graph & RAG - Index Creation and Vector Store - Embeddings Chevron down icon Chevron up icon
Hands-on: User Cases - Graph Retrieval and RAG Systems - The Whole Flow Chevron down icon Chevron up icon
Wrap up Chevron down icon Chevron up icon
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