Machine Learning For Physicists

A hands-on approach

By: Sadegh Raeisi, Sedighe Raeisi

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Hardcover | 21 November 2023

At a Glance

Hardcover
236 Pages

Dimensions(cm)
25.4 x 17.78 x 1.42

Hardcover

RRP $253.00

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Machine learning is a branch of artificial intelligence (AI) which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy. It is an important component of the growing field of data science. Through the use of statistical methods, algorithms are trained to make classifications or predictions, uncovering key insights within data. For online shoppers, that means better "you might also like..." suggestions, but for scientists, it can facilitate scientific progress and reveal profound insights hiding in large datasets.
It is critical to educate our students with modern machine learning techniques and to give them the skill set required for the practical application of ML to their everyday research. 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.

Key Features:

Practical Hands-on approach: enables the reader to use machine learning

Includes code and accompanying on;-line resources

Practical examples for modern research and uses case studies

Written in a language accessible by physics students

Complete one-semester course

the aim is to take a novice and turn them into a student who not only understands the principles of ML but has the confidence and practical skillset to start to apply these tools themselves

Industry Reviews

Machine Learning for Physicists is a highly recommended resource for physics students eager to harness the power of machine learning in their research. Its practical orientation, relevant examples, and project-based learning approach make it an excellent starting point.

Dr. J. Rogel-Salazar, Contemporary Physics, Oct 2024

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