While there are some good picks (especially "An Introduction to Statistical Learning with Applications in R" and "Deep Learning with Python" by Chollet, the Keras author), I am surprised it is missing "Information Theory, Inference, and Learning Algorithms" by David MacKay (http://www.inference.org.uk/itila/book.html).
The "Bayesian Inference and Machine Learning" track gives a nice foundation to anything with "log loss". After that even k-means won't be an ad-hoc algorithm.
The "Bayesian Inference and Machine Learning" track gives a nice foundation to anything with "log loss". After that even k-means won't be an ad-hoc algorithm.