Chapter 1.8: Components of a Learner

Nearly all supervised learning algorithms can be described in terms of three components: 1) hypothesis space, 2) risk, and 3) optimization. In this section, we explain how these components work together and why this is a very useful concept for many supervised learning approaches.

1Video Lecture

2Slides

3Quiz