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Graph Data Science with Neo4j

You're reading from   Graph Data Science with Neo4j Learn how to use Neo4j 5 with Graph Data Science library 2.0 and its Python driver for your project

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Product type Paperback
Published in Jan 2023
Publisher Packt
ISBN-13 9781804612743
Length 288 pages
Edition 1st Edition
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Author (1):
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Estelle Scifo Estelle Scifo
Author Profile Icon Estelle Scifo
Estelle Scifo
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Table of Contents (16) Chapters Close

Preface 1. Part 1 – Creating Graph Data in Neo4j
2. Chapter 1: Introducing and Installing Neo4j FREE CHAPTER 3. Chapter 2: Importing Data into Neo4j to Build a Knowledge Graph 4. Part 2 – Exploring and Characterizing Graph Data with Neo4j
5. Chapter 3: Characterizing a Graph Dataset 6. Chapter 4: Using Graph Algorithms to Characterize a Graph Dataset 7. Chapter 5: Visualizing Graph Data 8. Part 3 – Making Predictions on a Graph
9. Chapter 6: Building a Machine Learning Model with Graph Features 10. Chapter 7: Automatically Extracting Features with Graph Embeddings for Machine Learning 11. Chapter 8: Building a GDS Pipeline for Node Classification Model Training 12. Chapter 9: Predicting Future Edges 13. Chapter 10: Writing Your Custom Graph Algorithms with the Pregel API in Java 14. Index 15. Other Books You May Enjoy

Importing CSV data into Neo4j with Cypher

The comma-separated values (CSV) file format is the most widely used to share data among data scientists. According to the dataset of Kaggle datasets (https://www.kaggle.com/datasets/morriswongch/kaggle-datasets), this format represents more than 57% of all datasets in this repository, while JSON files account for less than 10%. It is popular for the following reasons:

  • How it resembles the tabular data storage format (relational databases)
  • Its closeness to the machine learning world of vectors and matrices
  • Its readability – you usually just have to read column names to understand what it is about (of course, a more detailed description is required to understand how the data was collected, the unit of physical quantities, and so on) and there are no hidden fields (compared to JSON, where you can only have a key existing from the 1,000th record and later, which is hard to know without a proper description or advanced data...
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