Scifo 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
1. Auflage 2023
ISBN: 978-1-80461-490-7
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 288 Seiten

No detailed description available for "Graph Data Science with Neo4j".

Autoren/Hrsg.

Scifo, Estelle

Fachgebiete

• Mathematik | Informatik Mathematik Mathematik Allgemein Diskrete Mathematik, Kombinatorik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle

Inhaltsverzeichnis

Table of Contents - Introducing and Installing Neo4j
- Using Existing Data to Build a Knowledge Graph
- Characterizing a Graph Dataset
- Using Graph Algorithms to Characterize a Graph Dataset
- Visualizing Graph Data
- Building a Machine Learning Model with Graph Features
- Automatically Extracting Features with Graph Embeddings for Machine Learning
- Building a GDS Pipeline for Node Classification Model Training
- Predicting Future Edges
- Writing Your Custom Graph Algorithm with the Pregel API

Über Autor(innen)

Scifo Estelle:

Estelle Scifo possesses over 7 years experience as a data scientist, after receiving her PhD from the Laboratoire de lAcclrateur Linaire, Orsay (affiliated to CERN in Geneva). As a Neo4j certified professional, she uses graph databases on a daily basis and takes full advantage of its features to build efficient machine learning models out of this data. In addition, she is also a data science mentor to guide newcomers into the field. Her domain expertise and deep insight into the perspective of the beginners needs make her an excellent teacher.