Chapter 7. Supervised and Unsupervised Learning
The amount of data collected for various purposes in society has increased enormously in the last few decades. Machine learning is a way of making sense of all this data by leveraging what we know about the data. In the generalized picture of machine learning, the computer first learns from a given dataset (training) and creates a generalized model to represent it. With this model, it is possible to predict various outcomes, results, and groupings (classes). In this chapter, we will cover the following topics:
- Linear regression with machine learning algorithms
- Clustering with machine learning algorithms
- Feature selection—a preprocessing method to select what is most important
- Classification with different machine learning algorithms and kernels
Before getting started, I will give you a brief introduction to machine learning and the package that we will use: Scikit-learn.
Introduction to machine learning
There are three main categories...
