Machine Learning Algorithms

Summary

In this chapter, we have introduced some main concepts about machine learning. We started with some basic mathematical definitions, to have a clear view about data formats, standards, and kind of functions. This notation will be adopted in all the other chapters and it's also the most diffused in technical publications. We discussed how scikit-learn seamlessly works with multi-class problems, and when a strategy is preferable to another.

The next step was the introduction of some fundamental theoretical concepts about learnability. The main questions we tried to answer were: how can we decide if a problem can be learned by an algorithm and what is the maximum precision we can achieve. PAC learning is a generic but powerful definition ...