I read Lantz’s Machine Learning with R. It is a rather decent introduction to what it says. The first chapters are an introduction on R and a tiny one on ML. Then it goes into several classification algorithms. There are some chapters on clustering, decision trees, the usual stuff. I got most profit from the chapter on neural networks and the final topics on model performance. I wish the book had gone deeper into some R packages, but I suppose the author wanted to keep it open for those who were just getting into ML.

Now I am delving into Goodfellow’s Deep Learning and I am enjoying it. First I was just trying the on-line version, but I got now the paper one: this is a good reference, with the right amount of theory and practice.