The Elements of Statistical Learning, by Hastie, Tibshirani, and Friedman, gives a lucid, practical description of the mathematical underpinnings of machine learning. Anyone aspiring to do more than mindlessly apply machine learning algorithms as black boxes ought to have a well-thumbed copy of this book.

Scala for Machine Learning, by Patrick R. Nicholas, describes practical implementations of many useful machine learning algorithms in Scala.

The Breeze documentation (https://github.com/scalanlp/breeze/wiki/Quickstart), API docs (http://www.scalanlp.org/api/breeze/#package), and source code (https://github.com/scalanlp/breeze) provide the most up-to-date sources of documentation on Breeze.