Machine Learning For Physicists: A hands-on approach

Bys: Raeisi, Sadegh and Raeisi, Sedighe

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

• Format: Hardcover
• Language: English
• ISBN: 0750349557
• ISBN13: 9780750349550
• Release Date: November 2023
• Publisher: Institute of Physics Publishing
• Length: 233 Pages
• Weight: 1.38 lbs.
• Dimensions: 0.6" x 7.0" x 10.0"