Download the free Kindle app and start reading Kindle books instantly on your smartphone, tablet, or computer - no Kindle device required.
Read instantly on your browser with Kindle for Web.
Using your mobile phone camera - scan the code below and download the Kindle app.
Follow the author
Report an issue with this product or sellerFrequently bought together
Customers who viewed this item also viewed
- Domain-Specific Small Language Models: Efficient AI for local deploymentPaperbackFREE Shipping by AmazonGet it as soon as Monday, Sep 21
- Build a Reasoning Model (From Scratch)PaperbackFREE Shipping by AmazonGet it as soon as Sunday, Sep 20
- Build a Large Language Model (From Scratch)PaperbackFREE Shipping by AmazonGet it as soon as Sunday, Sep 20
- AI Agents and Applications: With LangChain, LangGraph, and MCPPaperbackFREE Shipping by AmazonGet it as soon as Monday, Sep 21
- AI Agents in Action, Second Edition: Intelligent workflows with LLMs, MCP, A2A, and morePaperbackFREE Shipping by AmazonGet it as soon as Monday, Sep 21
- AI Engineering: Building Applications with Foundation ModelsPaperbackFREE Shipping by AmazonGet it as soon as Sunday, Sep 20
Customers also bought or read
- Reinforcement Learning from Human Feedback: LLM alignment and post-training
Just releasedPaperback$59.99
From the Publisher
“Builds understanding both at a theoretical and a practical level.”
Corey L. Lanum, Visualization Partners
“An excellent introduction to building KG and LLM-powered applications.”
Dave Bechberger, Author of Graph Databases in Action
“Comprehensive and well thought out! The authors hit it out of the park again.”
Sujit Pal, Elsevier
why this book?
Knowledge Graphs and LLMs in Action provides a practical guide to combining structured knowledge graphs with LLMs, showing you how to build, enrich, and exploit graphs in tandem with large language models to gain better context, reasoning, and explainability.
You get hands-on techniques, code, and best practices across all stages—labeling data, modeling the graph, linking to LLM outputs—so you can apply these concepts in real systems.
The synergy helps mitigate common LLM weaknesses—like hallucinations or lack of factual grounding—by anchoring their outputs in explicit relational structure.
about Manning
Manning helps developers and tech professionals stay ahead in a fast-moving industry with expert-led books, videos, and projects. Learning never stops, but it’s hard to keep up, so we focus on content that’s practical, clear, and trusted. As an independent publisher, we adapt quickly, from pioneering early-access books to offering DRM-free eBooks. Our series, like "In Action" and "In a Month of Lunches", reflect a commitment to making complex topics accessible.
Build a Large Language Model (From Scratch)
|
AI Agents in Action
|
Natural Language Processing in Action, Second Edition
|
LLMs in Production: From language models to successful products
|
Data Analysis with LLMs: Text, tables, images and sound (In Action)
|
Causal AI
|
|
|---|---|---|---|---|---|---|
| Customer Reviews |
613
|
51
|
8
|
36
|
7
|
14
|
| Level of proficiency | Intermediate | Intermediate | Intermediate | Intermediate | Intermediate | Advanced |
| About the reader | Readers need intermediate Python skills and some knowledge of machine learning. | For intermediate Python programmers. | For intermediate Python programmers. | For data scientists and ML engineers. | For data scientists and data analysts. | For data scientists and machine learning engineers. |
| Special features | Includes liveBook with out built-in AI assistant. | Includes liveBook with out built-in AI assistant. | Includes liveBook with out built-in AI assistant. | Includes liveBook with out built-in AI assistant. | Includes liveBook with out built-in AI assistant. | Includes liveBook with out built-in AI assistant. |
| Pages | 368 | 344 | 688 | 456 | 232 | 520 |
About the author
Product Videos
