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Thoughtful Machine Learning by Matthew Kirk

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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, it’s a subject that is often defined in a somewhat vague way. In this quick introduction, we’ll go over what exactly machine learning is, as well as 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 will extract patterns out of data. Generally speaking, there are a few problems machine learning tackles; these are listed in Table 2-1 and described in the subsections that follow.

Table 2-1. The problems of machine learning

The 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

Playing a game with rewards and payoffs

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.

Figure 2-1. This shows a line fitted to some ...

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