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Graph Algorithms for Data Science

by Tomaz Bratanic

The book of the week from 26 Sep 2022 to 30 Sep 2022

Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with practical examples and concrete advice on implementation and deployment.

In Graph Algorithms for Data Science you will learn:

  • Labeled-property graph modeling
  • Constructing a graph from structured data such as CSV or SQL
  • NLP techniques to construct a graph from unstructured data
  • Cypher query language syntax to manipulate data and extract insights
  • Social network analysis algorithms like PageRank and community detection
  • How to translate graph structure to a ML model input with node embedding models
  • Using graph features in node classification and link prediction workflows

Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It’s filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You’ll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. 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.

To take part in the book of the week event:

  • Register in our Slack
  • Join the #book-of-the-week channel
  • Ask as many questions as you'd like
  • The book authors answer questions from Monday till Thursday
  • On Friday, the authors decide who wins free copies of their book

To see other books, check the the book of the week page.

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