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Название: Graph Algorithms for Data Science (MEAP v7)
Автор: Tomaz Bratanic
Издательство: Manning Publications
Год: 2023
Страниц: 386
Язык: английский
Формат: pdf, epub
Размер: 18.1 MB
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. 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. For data scientists who know the basics of Machine Learning. Examples use the Cypher query language, which is explained in the book.
Автор: Tomaz Bratanic
Издательство: Manning Publications
Год: 2023
Страниц: 386
Язык: английский
Формат: pdf, epub
Размер: 18.1 MB
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. 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. For data scientists who know the basics of Machine Learning. Examples use the Cypher query language, which is explained in the book.