Neuware - This book presents ML concepts with a hands-on approach for physicists. The goal is to both educate and enable a larger part of the community with these skills. This will lead to wider applications of modern ML techniques in physics. Accessible to physical science students, the book assumes a familiarity with statistical physics but little in the way of specialised computer science background. All chapters start with a simple introduction to the basics and the foundations, followed by some examples and then proceeds to provide concrete examples with associated codes from a GitHub repository. Many of the code examples provided can be used as is or with suitable modification by the students for their own applications.Key Features: - Practical Hands-on approach: enables the reader to use machine learning - Includes code and accompanying online resources - Practical examples for modern research and uses case studies - Written in a language accessible by physics students - Complete one-semester course.

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Bibliographic Details

Title: Machine Learning For Physicists : A hands-on approach
Publisher: IOP Publishing Ltd Nov 2023
Publication Date: 2023
Language: English
ISBN 10: 0750349557
ISBN 13: 9780750349550
Binding: Buch
Condition: Neu
Dimensions: 254 millimeters width by 178 millimeters height by 14 millimeters depth
Weight: 626 grams

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This book presents ML concepts with a hands-on approach for physicists. The book aims to enable its readers to understand the approaches available to them and to equip them to be able to apply these techniques to their research problems.

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