I am planing 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 of 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 context of Physics?