Tomaz Bratanic

Essential GraphRAG

Knowledge Graph-Enhanced RAG teaches you to implement accurate, performant, and traceable RAG by structuring the context data as a knowledge graph. Filled with practical techniques, this book teaches you how to build RAG on both unstructured and structured data. You’ll go hands-on to build a vector similarity search retrieval tool, an Agentic RAG application, extract information from text to create a Knowledge Graph, evaluate performance and accuracy, and more.

Graphs and Network Science: An Introduction

Featuring Chapter 1 from Manning’s upcoming book, Graph Data Science by Tomaz Bratanic, this free mini ebook lays the first bricks in your graph data science foundation with an introduction to network science, graphs, and graph analytics. Through illuminating examples, beautifully detailed images, and the author’s clear and passionate explanations, you’ll appreciate the amazing connections all around us and be eager to take the next step in your graph data science journey.

Graph Algorithms for Data Science

Graph Algorithms for Data Science shows you how to construct and analyze graphs from structured and unstructured data. In it, you’ll learn to apply graph algorithms like PageRank, community detection/clustering, and knowledge graph models by putting each new algorithm to work in a hands-on data project. This cutting-edge book also demonstrates how you can create graphs that optimize input for AI models using node embedding.