Hands-On Graph Analytics with Neo4j: Perform graph processing and visualization

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Estado
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Book Title
Hands-On Graph Analytics with Neo4j: Perform graph processing and
ISBN
9781839212611
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Product Identifiers

Publisher
Packt Publishing, The Limited
ISBN-10
1839212616
ISBN-13
9781839212611
eBay Product ID (ePID)
21050398988

Product Key Features

Number of Pages
510 Pages
Language
English
Publication Name
Hands-On Graph Analytics with Neo4j : Perform Graph Processing and Visualization Techniques Using Connected Data Across Your Enterprise
Subject
Data Modeling & Design, Data Processing, Databases / General
Publication Year
2020
Type
Textbook
Subject Area
Computers
Author
Estelle Scifo
Format
Trade Paperback

Dimensions

Item Length
3.6 in
Item Width
3 in

Additional Product Features

Intended Audience
Trade
Dewey Edition
23
Dewey Decimal
005.74
Table Of Content
Table of Contents Graph Databases The Cypher Query Language Empowering Your Business with Pure Cypher The Graph Data Science Library and Path Finding Spatial Data Node Importance Community Detection and Similarity Measures Using Graph-based Features in Machine Learning Predicting Relationships Graph embedding - from Graphs to Matrices Using Neo4j in Your Web Application Neo4j at Scale
Synopsis
To start with you will cover the basics of graph analytics, Cypher querying language, components of graph architecture, and more. You will implement Neo4j techniques to understand various graph analytics methods to reveal complex relationships in data. You will understand how machine learning can be used to perform smarter graph analytics., Discover how to use Neo4j to identify relationships within complex and large graph datasets using graph modeling, graph algorithms, and machine learning Key Features Get up and running with graph analytics with the help of real-world examples Explore various use cases such as fraud detection, graph-based search, and recommendation systems Get to grips with the Graph Data Science library with the help of examples, and use Neo4j in the cloud for effective application scaling Book Description Neo4j is a graph database that includes plugins to run complex graph algorithms. The book starts with an introduction to the basics of graph analytics, the Cypher query language, and graph architecture components, and helps you to understand why enterprises have started to adopt graph analytics within their organizations. You'll find out how to implement Neo4j algorithms and techniques and explore various graph analytics methods to reveal complex relationships in your data. You'll be able to implement graph analytics catering to different domains such as fraud detection, graph-based search, recommendation systems, social networking, and data management. You'll also learn how to store data in graph databases and extract valuable insights from it. As you become well-versed with the techniques, you'll discover graph machine learning in order to address simple to complex challenges using Neo4j. You will also understand how to use graph data in a machine learning model in order to make predictions based on your data. Finally, you'll get to grips with structuring a web application for production using Neo4j. By the end of this book, you'll not only be able to harness the power of graphs to handle a broad range of problem areas, but you'll also have learned how to use Neo4j efficiently to identify complex relationships in your data. What you will learn Become well-versed with Neo4j graph database building blocks, nodes, and relationships Discover how to create, update, and delete nodes and relationships using Cypher querying Use graphs to improve web search and recommendations Understand graph algorithms such as pathfinding, spatial search, centrality, and community detection Find out different steps to integrate graphs in a normal machine learning pipeline Formulate a link prediction problem in the context of machine learning Implement graph embedding algorithms such as DeepWalk, and use them in Neo4j graphs Who this book is for This book is for data analysts, business analysts, graph analysts, and database developers looking to store and process graph data to reveal key data insights. This book will also appeal to data scientists who want to build intelligent graph applications catering to different domains. Some experience with Neo4j is required.

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