Hands-On Graph Analytics with Neo4j: Perform graph processing and visualization techniques using connected data across your enterprise

Disclaimer: The Publisher asked me to review this book and sent me a review copy. I promise to be completely honest about my thoughts on this book.This book describes the concepts of Neo4j with good examples, specially I liked the example of comparing data with water, a container with database and it very nicely explained the way of choosing an appropriate container based on need.Further this book also gives us a clear understanding on Cypher Query Language with sample code. Covered almost all of the concepts starting from creating a node to managing it and modify / update them, including loading the data from CSV or JSON format or web APIs. From time-to-time the author has also taken care of comparing Neo4j with other database terminology and shared related terms considering that this book will also be read by various database users, and it made me more comfortable when doing comparison with the database I am used to. In this book the author has demonstrated the power of Neo4j by building a knowledge graph from unstructured data with detailed explanation of geographic coordinate systems. Which is very hard to do with various other databases. Author did not leave us with just the concepts and hands-on with Neo4j, she also taken us from novice to expert and included Data Science/Machine Learning portion as well which is booming now!Another important thing I liked is that the author has taken care of small concepts & tips and has explained them clearly, as they are the building blocks. Along with this, there are some exercises to test the understanding. "Tip" section in the book is awesome, as it contains very important tips which one has to keep them handy. This book is worth reading irrespective who you are, be it a Beginner (to gain fundamental knowledge on Neo4j); Full-stack developer (Where and when to use Neo4j with Python or any other language); database developer (how to create; manage and maintain database); or a data scientist & ML engineer (Data Analysis and Prediction with Python and Neo4j); etc. It covers all aspects of Neo4j.I loved reading this book.

This book offers a solid introduction to Neo4j. It sometimes gets off track, getting into the weeds of topics like user authentication in Flask, but overall it's worth the read if you want to learn about graph databases. Code examples use a range of languages, including Cypher, JavaScript, Python, and even SparQL.

I received a copy of this book from the publisher so that I could review it.This book does a great job of introducing a range of graph-related topics along with code examples to illustrate the points. It is a practical guide written by someone who is well grounded in theory. The author's experience as a data scientist helps her bring together various tools in the Neo4j ecosystem that you might use on a real project. You aren't just getting a single vendor's sales pitch. Sometimes data scientists struggle with the ML Ops required to turn a great model into a production tool. The book takes the reader all the way through ideas for deploying graph analytics in an application and tuning the database in production. This sets the book apart from others that I have read on applied graph analytics.The section on spatial data is especially well done, as the author has been a major contributor to the Neo4j community in that area. The chapters on machine learning are also deep and valuable.In order to explain graph algorithms, the book provides examples in pure Python before showing the way to call Neo4j's implementation. I found myself skimming/skipping the pure Python explanations since Neo4j provides these algorithms out of the box.The book attempts to explain concepts from the ground up, but you will get more from this book if you have some experience with machine learning, Neo4j, and Python. For a data scientist or analyst looking to add to graph analytics to your tool kit, this will be a valuable resource and a source of inspiration.

Disclaimer: The publisher asked me to review this book and gave me a review copy.I am mostly interested in the data science aspect of the graph data so I skimmed the chapters related to graph query or using Neo4j in production.Overview: The book covers almost everything related to graph data including- The theory of the graph data, how to set it up and the query language cypher- Graph algorithms- Feature generation and embedding techniques to use with machine learning- Using Neo4j for productionPros:- It covers a almost everything you can do with graph data such as visualization, analysis, feature engineering etc.- Provides ample techniques on how generate information based on the nodes and edges of a graph to use as a feature in machine learning.- It talks about how to use Neo4j in production at scaleCons:- If i have to write a con I can say: I would love to see more examples on graph algorithms section and machine learning on graphs section. There is a lot information in these two sections and after some time it feels like reading the same topic from a different perspective. Narrowing down a bit and supporting with more usecases would make the book more practical and less theoretical.

Estelle did a great job introducing Neo4j from the lenses of graph analytics.

Estelle's book is an incredibly clear breakdown of how to make the most out of Neo4j and all it's capabilities. She does a fantastic job of explaining how to conceptualize "graphy" problems and then use Neo4j to solve them. If you're new to graphs and Neo4j or if you're an experienced graphista, this books is going to have something for you.

Atende ao que preciso, sobre a aplicação da Teoria dos Grafos na Computação. Não encontrei falhas, até o momento.

Estelle goes straight to the point in her book she manages to pick up beginners as well as seniors, which she does by clearly and comprehensively building up the respective theoretical aspects with a direct forwarding to the implementation and engineering part. Pure hands-on!For me as an engineer who must jump from project to project the practical part and the implementation is relevant. Thanks to the book I have taken new aspects of Neo4j with me that have been directly incorporated into two business projects.Estelle also has a heart for Natural Language Processing! Language and its construction are based on relationships and so the connection is obvious. Using spaCy to construct Cypher queries for Neo4j from pure written English – wonderful!This book is a must-read for anyone who wants a quick and straight forward introduction to Graph Technology with Neo4j and its practical implementations.

I was following along okay but when it came to the part for "Empowering your business with pure cypher" the examples did not work, pointed to websites where the downloads did not exists.Seems this book needs an update