While there are some good picks (especially "An Introduction to Statistical Learning with Applications in R" and "Deep Learning with Python" by Chollet, the Ker

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 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.