Machine Learning in Action

Part 4. Additional tools

This fourth and final part of Machine Learning in Action covers some additional tools that are commonly used in practice and can be applied to the material from the first three parts of the book. The tools cover dimensionality-reduction techniques, which you can use to preprocess the inputs before using any of the algorithms from the first three parts of this book. This part also covers map reduce, which is a technique for distributing jobs to thousands of machines.

Dimensionality reduction is the task of reducing the number of inputs you have; this can reduce noise and improve the performance of machine learning algorithms. chapter 13 is the first chapter on dimensionality reduction; we look at principal component analysis, ...