Graph Data Science with Python and Neo4j

Timothy Eastridge

ISBN 10: 8197081964 / ISBN 13: 9788197081965

Published by Orange Education Pvt Ltd, 2024

About this Item

Graph Data Science with Python and Neo4j | Timothy Eastridge | Taschenbuch | Englisch | 2024 | Orange Education Pvt Ltd | EAN 9788197081965 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Seller Inventory # 128790070

Bibliographic Details

• Title: Graph Data Science with Python and Neo4j
• Publisher: Orange Education Pvt Ltd
• Publication Date: 2024
• Language: English
• ISBN 10: 8197081964
• ISBN 13: 9788197081965
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 191H x 11D millimeters 235 millimeters width by 191 millimeters height by 11 millimeters depth
• Weight: 370 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Practical approaches to leveraging graph data science to solve real-world challenges.

Book Description
Graph Data Science with Python and Neo4j is your ultimate guide to unleashing the potential of graph data science by blending Python's robust capabilities with Neo4j's innovative graph database technology. From fundamental concepts to advanced analytics and machine learning techniques, you'll learn how to leverage interconnected data to drive actionable insights. Beyond theory, this book focuses on practical application, providing you with the hands-on skills needed to tackle real-world challenges.

You'll explore cutting-edge integrations with Large Language Models (LLMs) like ChatGPT to build advanced recommendation systems. With intuitive frameworks and interconnected data strategies, you'll elevate your analytical prowess.

This book offers a straightforward approach to mastering graph data science. With detailed explanations, real-world examples, and a dedicated GitHub repository filled with code examples, this book is an indispensable resource for anyone seeking to enhance their data practices with graph technology. Join us on this transformative journey across various industries, and unlock new, actionable insights from your data.

Table of Contents
1. Introduction to Graph Data Science
2. Getting Started with Python and Neo4j
3. Import Data into the Neo4j Graph Database
4. Cypher Query Language
5. Visualizing Graph Networks
6. Enriching Neo4j Data with ChatGPT
7. Neo4j Vector Index and Retrieval-Augmented Generation (RAG)
8. Graph Algorithms in Neo4j
9. Recommendation Engines Using Embeddings
10. Fraud Detection
CLOSING SUMMARY
The Future of Graph Data Science
Index