Basics of scikit-learn

Now, let's focus on scikit-learn, an essential ML library for Python. It implements dozens of classic ML models, but also numerous tools to help you while training them, such as pre-processing methods and cross-validation.

The first thing you must do to get started is install it in your Python environment:

$ pip install scikit-learn

We can now start our scikit-learn journey!

Training models and predicting

In scikit-learn, ML models and algorithms are called estimators. Each is a Python class that implements the same methods. In particular, we have fit, which is used to train a model, and predict, which is used to run the trained model on new data.

To try this, we'll load a sample dataset. scikit-learn comes with a few toy datasets that are very useful for performing experiments. You can find out more about them in the official documentation: https://scikit-learn.org/stable/datasets.html.

Here, we'll use the digits dataset,...