You're reading from Machine Learning with PyTorch and Scikit-Learn

Product typeBook

Published inFeb 2022

PublisherPackt

ISBN-139781801819312

Edition1st Edition

Concepts

Machine Learning

Authors (3):

Sebastian Raschka

Yuxi (Hayden) Liu

Vahid Mirjalili

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Introduction to graph data

Broadly speaking, graphs represent a certain way we describe and capture relationships in data. Graphs are a particular kind of data structure that is nonlinear and abstract. And since graphs are abstract objects, a concrete representation needs to be defined so the graphs can be operated on. Furthermore, graphs can be defined to have certain properties that may require different representations. Figure 18.1 summarizes the common types of graphs, which we will discuss in more detail in the following subsections:

Figure 18.1: Common types of graphs

Undirected graphs

An undirected graph consists of nodes (in graph theory also often called vertices) that are connected via edges where the order of the nodes and their connection does not matter. Figure 18.2 sketches two typical examples of undirected graphs, a friend graph, and a graph of a chemical molecule consisting of atoms connected through chemical bonds (we will be discussing such molecular...

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Machine Learning with PyTorch and Scikit-Learn

Published in: Feb 2022Publisher: PacktISBN-13: 9781801819312

Authors (3)

Sebastian Raschka

Sebastian Raschka is an Assistant Professor of Statistics at the University of Wisconsin-Madison focusing on machine learning and deep learning research. As Lead AI Educator at Grid AI, Sebastian plans to continue following his passion for helping people get into machine learning and artificial intelligence.
Read more about Sebastian Raschka

Yuxi (Hayden) Liu

Yuxi (Hayden) Liu was a Machine Learning Software Engineer at Google. With a wealth of experience from his tenure as a machine learning scientist, he has applied his expertise across data-driven domains and applied his ML expertise in computational advertising, cybersecurity, and information retrieval. He is the author of a series of influential machine learning books and an education enthusiast. His debut book, also the first edition of Python Machine Learning by Example, ranked the #1 bestseller in Amazon and has been translated into many different languages.
Read more about Yuxi (Hayden) Liu

Vahid Mirjalili

Vahid Mirjalili is a deep learning researcher focusing on CV applications. Vahid received a Ph.D. degree in both Mechanical Engineering and Computer Science from Michigan State University.
Read more about Vahid Mirjalili

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You're reading from Machine Learning with PyTorch and Scikit-Learn

Introduction to graph data

Undirected graphs

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Authors (3)

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