Resource recommendation for machine learning

Question

I am planning to change my field (in PhD) and learn Machine Learning to differentiate different phases of strongly correlated matter. I learned Monte Carlo method in my MS and have intermediate level knowledge of topological insulators.
Before completely getting into Machine Learning, I want to go-through an introductory level book/article on Machine learning for physicists. I want to know if it is too difficult for me to learn. (is it really very difficult?)
Do you know any books/articles in which Machine Learning is explained in the context of Physics?

stock · Answer

The following book might help you.
It covers the following:

Supervised Machine Learning Algorithms
Unsupervised Machine
Learning Algorithms
Semi Supervised Machine Learning Algorithms
Random Forest Algorithms
Support Vector Machine Algorithms
Artificial Neural Network Algorithms
Regression Algorithms
Clustering Algorithms
Resampling Algorithms
Association Rule Algorithm

Reference:

Machine Learning: An overview with the help of R software
ISBN: 978-1790122622
https://books.google.com/books/about/Machine_Learning_An_overview_with_the_he.html?id=NDF7DwAAQBAJ

user278970 · Answer

To start with this domain, first of all you should be working with Python Programming. In Python, the dedicated library for ML is available like SCIKIT-LEARN

Resource recommendation for machine learning

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