Graphs are the natural way to represent and understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with concrete advice on implementation and deployment. You don’t need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects.
Guest: Tomaz Bratanic
Book: https://www.manning.com/books/graph-algorithms-for-data-science
35% off with code: au35bra
Blog: https://medium.com/@bratanic-tomaz
Neo4j Graph Data Science: https://bit.ly/45V0WMU
Sandbox https://dev.neo4j.com/try
Code Examples: https://github.com/tomasonjo/graphs-network-science/tree/main
0:00 Intro
15:20 Chapter Overview
24:25 Chapter 1
34:30 Graph Algorithms with Twitter Dataset
43:00 Relationships between entities ( co-occurrence)
52:10 Q&A
1:00:30 Wrap-Up
#neo4j #graphdatabase #datascience #algorithm #python