Knowledge graphs are a pivotal building block for designing intelligent systems for empowering advanced analytics and decision making. Knowledge Graphs and LLMs In Action is a practical guide complete with techniques, code samples and use cases, allowing you to leverage the connected nature of various data sources and simultaneously incorporate human knowledge. Knowledge graphs facilitate creation of solutions which are highly valued by engineers, data scientists and CEOs alike.
What’s inside
- Model knowledge graphs with an iterative top-down approach based in business needs
- Create a knowledge graph starting from ontologies, taxonomies, and structured data
- Build knowledge graphs from unstructured data sources using LLMs
- Use machine learning algorithms to complete your graphs and derive insights from it
- Reason on the knowledge graph and build KG-powered RAG systems for LLMs
Meet the authors
All the authors have extensive experience in the domain of building and analysing knowledge graphs. Together they cover expertise in engineering, research, data science and consultancy, all delivered for and with clients operating in a wide span of industries all around the world. Currently they are contributing to building an enterprise-level product for mission-critical graph analytics – GraphAware Hume.
Alessandro Negro
Chief Scientist
Fabio Montagna
Lead Machine Learning Engineer
In Knowledge Graphs and LLMs in Action, you’ll dive into the theory of knowledge graphs and learn how to apply them alongside large language models (LLMs) to build real-world intelligence systems.
The book takes you from creating knowledge graphs from first principles to developing intelligent advisor applications for domains like healthcare and finance, and even constructing retrieval-augmented generation (RAG) pipelines for LLMs.
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