Getting started with scikit-learn
In this recipe, we introduce the basics of the machine learning scikit-learn package (http://scikit-learn.org). This package is the main tool we will use throughout this chapter. Its clean API makes it easy to define, train, and test models.
We will show here a basic example of linear regression in the context of curve fitting. This toy example will allow us to illustrate key concepts such as linear models, overfitting, underfitting, regularization, and cross-validation.
Getting ready
You can find all instructions to install scikit-learn in the main documentation. For more information, refer to http://scikit-learn.org/stable/install.html. Anaconda comes with scikit-learn by default, but, if needed, you can install it manually by typing conda install scikit-learn in a Terminal.
How to do it...
We will generate a one-dimensional dataset with a simple model (including some noise), and we will try to fit a function to this data. With this function, we can predict...
