Practical considerations before modeling

We now have a basic understanding of some of the most important conceptual and theoretical aspects of ML. In this section, we will talk about some of the practical things we need to do before building a model; this includes some further data processing that is needed for feeding the data for model training. We will also introduce our main tool for model building: scikit-learn.

Introducing scikit-learn

If you go to the main web page of scikit-learn, the first things you will read are the following statements about it:

• Simple and efficient tool for data mining and data analysis
• Accessible to everybody, and reusable in various contexts
• Built on NumPy, SciPy, and matplotlib
• Open source...