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Graph Data Science with Python and Neo4j: Hands-on Projects on Python and Neo4j Integration for Data Visualization and Analysis Using Graph Data Science for Building Enterprise Strategies by Timothy Eastridge at Abbey's Bookshop,
Graph Data Science with Python and Neo4j: Hands-on Projects on Python and Neo4j Integration for Data Visualization...
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Timothy Eastridge

Graph Data Science with Python and Neo4j

Hands-on Projects on Python and Neo4j Integration for Data Visualization and Analysis Using...

Timothy Eastridge

$80.95   $69.01

Undefined

Not in-store but you can order this
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English
Orange Education Pvt Ltd
11 March 2024
Games development & programming
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
By:  
Imprint:   Orange Education Pvt Ltd
Edition:   New edition
ISBN:   9788197081965
ISBN 10:   8197081964
Pages:   192
Publication Date:  
Audience:   Adult education ,  Tertiary & Higher Education
Format:   Undefined
Publisher's Status:   Active

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