Machine Learning for Physicists by Sadegh Raeisi (.PDF)

File Size: 32.8 MB

Machine Learning for Physicists: A hands-on approach by Sadegh Raeisi, Sedighe Raeisi
Requirements: .PDF reader, 32.8 MB
Overview: This book presents Machine Learning (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. For this book, basic familiarity with programming and basic Python syntaxes are essential. Additionally, there are libraries such as NumPy, Pandas, and Matplotlib that are extremely helpful for handling and visualization of the data and are used frequently in this context. The reader is thus encouraged to become familiar with them.
Genre: Non-Fiction > Tech & Devices

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