Chapter 2. A Quick Introduction to Machine Learning

You’ve picked up this book because you’re interested in machine learning. While you probably have an idea of what machine learning is, the subject is often defined somewhat vaguely. In this quick introduction, I’ll go over what exactly machine learning is, and provide a general framework for thinking about machine learning algorithms.

What Is Machine Learning?

Machine learning is the intersection between theoretically sound computer science and practically noisy data. Essentially, it’s about machines making sense out of data in much the same way that humans do.

Machine learning is a type of artificial intelligence whereby an algorithm or method extracts patterns from data. Machine learning solves a few general problems; these are listed in Table 2-1 and described in the subsections that follow.

Table 2-1. The problems that machine learning can solve
Problem Machine learning category

Fitting some data to a function or function approximation

Supervised learning

Figuring out what the data is without any feedback

Unsupervised learning

Maximizing rewards over time

Reinforcement learning

Supervised Learning

Supervised learning, or function approximation, is simply fitting data to a function of any variety. For instance, given the noisy data shown in Figure 2-1, you can fit a line that generally approximates it.

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Figure ...

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