Neo4j A Graph Project Story

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Neo4j A Graph Project Story

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Author : Sylvain Roussy
language : en
Publisher:
Release Date : 2019-05-13

Neo4j A Graph Project Story written by Sylvain Roussy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-13 with categories.

You may already have an idea of what Neo4j is and how it works, and maybe you've even played around with some ideas using it. The question now is how you can take your graph project all the way to production-grade. This is what is discussed in this book. The book starts with a brief introduction to Neo4j and its query language, CYPHER, to help readers who are just beginning to explore Neo4j. Then we go straight to the subject in question: how to set up a real life project based on Neo4j, from the proof of concept to an operating production-grade graph database. We focus on methodology, integrations with existing systems, performance, monitoring and security. As experts from the Neo4j community, the authors have chosen an unusual format to transmit their technical know-how: they tell you a story, a graph project story, where the protagonists are members of a technical team who specializes in the representation and manipulation of strongly connected data. The plot starts when a client come in with his project. You will attend their working sessions and see how they develop the project, fight over approaches, and ultimately solve the problems they encounter. Welcome to GraphITs.Tech! This audacious and, we hope, entertaining approach allows you to experience all aspects of setting up a graph database, from the various and sometimes opposing points of view of technical and network experts, project managers, and even trainees.

Neo4j

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Author :
language : en
Publisher:
Release Date : 2019

Neo4j written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.

Graph Algorithms

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Author : Mark Needham
language : en
Publisher: O'Reilly Media
Release Date : 2019-05-16

Graph Algorithms written by Mark Needham and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-16 with Computers categories.

Discover how graph algorithms can help you leverage the relationships within your data to develop more intelligent solutions and enhance your machine learning models. You’ll learn how graph analytics are uniquely suited to unfold complex structures and reveal difficult-to-find patterns lurking in your data. Whether you are trying to build dynamic network models or forecast real-world behavior, this book illustrates how graph algorithms deliver value—from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. This practical book walks you through hands-on examples of how to use graph algorithms in Apache Spark and Neo4j—two of the most common choices for graph analytics. Also included: sample code and tips for over 20 practical graph algorithms that cover optimal pathfinding, importance through centrality, and community detection. Learn how graph analytics vary from conventional statistical analysis Understand how classic graph algorithms work, and how they are applied Get guidance on which algorithms to use for different types of questions Explore algorithm examples with working code and sample datasets from Spark and Neo4j See how connected feature extraction can increase machine learning accuracy and precision Walk through creating an ML workflow for link prediction combining Neo4j and Spark

Learning Cypher

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Author : Onofrio Panzarino
language : en
Publisher: Packt Publishing Ltd
Release Date : 2014-05-14

Learning Cypher written by Onofrio Panzarino and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-14 with Computers categories.

An easy-to-follow guide full of tips and examples of real-world applications. In each chapter, a thorough example will show you the concepts in action, followed by a detailed explanation. This book is intended for those who want to learn how to create, query, and maintain a graph database, or who want to migrate to a graph database from SQL. It would be helpful to have some familiarity with Java and/or SQL, but no prior experience is required.

Neo4j In Action

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Author : Tareq Abedrabbo
language : en
Publisher: Simon and Schuster
Release Date : 2014-12-05

Neo4j In Action written by Tareq Abedrabbo and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-05 with Computers categories.

Summary Neo4j in Action is a comprehensive guide to Neo4j, aimed at application developers and software architects. Using hands-on examples, you'll learn to model graph domains naturally with Neo4j graph structures. The book explores the full power of native Java APIs for graph data manipulation and querying. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Much of the data today is highly connected—from social networks to supply chains to software dependency management—and more connections are continually being uncovered. Neo4j is an ideal graph database tool for highly connected data. It is mature, production-ready, and unique in enabling developers to simply and efficiently model and query connected data. About the Book Neo4j in Action is a comprehensive guide to designing, implementing, and querying graph data using Neo4j. Using hands-on examples, you'll learn to model graph domains naturally with Neo4j graph structures. The book explores the full power of native Java APIs for graph data manipulation and querying. It also covers Cypher, Neo4j's graph query language. Along the way, you'll learn how to integrate Neo4j into your domain-driven app using Spring Data Neo4j, as well as how to use Neo4j in standalone server or embedded modes. Knowledge of Java basics is required. No prior experience with graph data or Neo4j is assumed. What's Inside Graph database patterns How to model data in social networks How to use Neo4j in your Java applications How to configure and set up Neo4j About the Authors Aleksa Vukotic is an architect specializing in graph data models. Nicki Watt, Dominic Fox, Tareq Abedrabbo, and Jonas Partner work at OpenCredo, a Neo Technology partner, and have been involved in many projects using Neo4j. Table of Contents PART 1 INTRODUCTION TO NEO4J A case for a Neo4j database Data modeling in Neo4j Starting development with Neo4j The power of traversals Indexing the data PART 2 APPLICATION DEVELOPMENT WITH NEO4J Cypher: Neo4j query language Transactions Traversals in depth Spring Data Neo4j PART 3 NEO4J IN PRODUCTION Neo4j: embedded versus server mode

Graph Databases

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Author : Ian Robinson
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-06-10

Graph Databases written by Ian Robinson and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-10 with Computers categories.

Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution. Model data with the Cypher query language and property graph model Learn best practices and common pitfalls when modeling with graphs Plan and implement a graph database solution in test-driven fashion Explore real-world examples to learn how and why organizations use a graph database Understand common patterns and components of graph database architecture Use analytical techniques and algorithms to mine graph database information

Graph Databases

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Author : Ian Robinson
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2015-06-10

Graph Databases written by Ian Robinson and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-10 with Computers categories.

Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. This second edition includes new code samples and diagrams, using the latest Neo4j syntax, as well as information on new functionality. Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution. Model data with the Cypher query language and property graph model Learn best practices and common pitfalls when modeling with graphs Plan and implement a graph database solution in test-driven fashion Explore real-world examples to learn how and why organizations use a graph database Understand common patterns and components of graph database architecture Use analytical techniques and algorithms to mine graph database information

Hands On Graph Analytics With Neo4j

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Author : Estelle Scifo
language : en
Publisher:
Release Date : 2020-08-21

Hands On Graph Analytics With Neo4j written by Estelle Scifo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-21 with Computers categories.

Graph Powered Machine Learning

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Author : Alessandro Negro
language : en
Publisher: Simon and Schuster
Release Date : 2021-10-05

Graph Powered Machine Learning written by Alessandro Negro and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-05 with Computers categories.

Upgrade your machine learning models with graph-based algorithms, the perfect structure for complex and interlinked data. Summary In Graph-Powered Machine Learning, you will learn: The lifecycle of a machine learning project Graphs in big data platforms Data source modeling using graphs Graph-based natural language processing, recommendations, and fraud detection techniques Graph algorithms Working with Neo4J Graph-Powered Machine Learning teaches to use graph-based algorithms and data organization strategies to develop superior machine learning applications. You’ll dive into the role of graphs in machine learning and big data platforms, and take an in-depth look at data source modeling, algorithm design, recommendations, and fraud detection. Explore end-to-end projects that illustrate architectures and help you optimize with best design practices. Author Alessandro Negro’s extensive experience shines through in every chapter, as you learn from examples and concrete scenarios based on his work with real clients! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Identifying relationships is the foundation of machine learning. By recognizing and analyzing the connections in your data, graph-centric algorithms like K-nearest neighbor or PageRank radically improve the effectiveness of ML applications. Graph-based machine learning techniques offer a powerful new perspective for machine learning in social networking, fraud detection, natural language processing, and recommendation systems. About the book Graph-Powered Machine Learning teaches you how to exploit the natural relationships in structured and unstructured datasets using graph-oriented machine learning algorithms and tools. In this authoritative book, you’ll master the architectures and design practices of graphs, and avoid common pitfalls. Author Alessandro Negro explores examples from real-world applications that connect GraphML concepts to real world tasks. What's inside Graphs in big data platforms Recommendations, natural language processing, fraud detection Graph algorithms Working with the Neo4J graph database About the reader For readers comfortable with machine learning basics. About the author Alessandro Negro is Chief Scientist at GraphAware. He has been a speaker at many conferences, and holds a PhD in Computer Science. Table of Contents PART 1 INTRODUCTION 1 Machine learning and graphs: An introduction 2 Graph data engineering 3 Graphs in machine learning applications PART 2 RECOMMENDATIONS 4 Content-based recommendations 5 Collaborative filtering 6 Session-based recommendations 7 Context-aware and hybrid recommendations PART 3 FIGHTING FRAUD 8 Basic approaches to graph-powered fraud detection 9 Proximity-based algorithms 10 Social network analysis against fraud PART 4 TAMING TEXT WITH GRAPHS 11 Graph-based natural language processing 12 Knowledge graphs

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

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Author : Timothy Eastridge
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2024-03-11

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 written by Timothy Eastridge and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-11 with Computers categories.

Practical approaches to leveraging graph data science to solve real-world challenges. Key Features ● Explore the fundamentals of graph data science, its importance, and applications. ● Learn how to set up Python and Neo4j environments for graph data analysis. ● Discover techniques to visualize complex graph networks for better understanding. 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. What you will learn ● Set up and utilize Python and Neo4j environments effectively for graph analysis. ● Import and manipulate data within the Neo4j graph database using Cypher Query Language. ● Visualize complex graph networks to gain insights into data relationships and patterns. ● Enhance data analysis by integrating ChatGPT for context-rich data enrichment. ● Explore advanced topics including Neo4j vector indexing and Retrieval-Augmented Generation (RAG). ● Develop recommendation engines leveraging graph embeddings for personalized suggestions. ● Build and deploy recommendation systems and fraud detection models using graph techniques. ● Gain insights into the future trends and advancements shaping the field of graph data science. 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