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Machine Learning, 2nd Edition by Stephen Marsland

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Chapter 2

Preliminaries

This chapter has two purposes: to present some of the overarching important concepts of machine learning, and to see how some of the basic ideas of data processing and statistics arise in machine learning. One of the most useful ways to break down the effects of learning, which is to put it in terms of the statistical concepts of bias and variance, is given in Section 2.5, following on from a section where those concepts are introduced for the beginner.

2.1 Some Terminology

We start by considering some of the terminology that we will use throughout the book; we’ve already seen a bit of it in the Introduction. We will talk about inputs and input vectors for our learning algorithms. Likewise, we will talk about the outputs ...

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