Machine Learning Foundations, Volume 1: Supervised Learning

Chapter 3. Introduction to Scikit-Learn

After exploring the fundamental concepts and theories of machine learning, we are now ready to put them into practice and build machine learning models to solve real-world problems.

Scikit-Learn is the main library in Python for constructing machine learning models that are not based on deep learning. It provides efficient implementations for a wide range of learning algorithms as well as an extensive set of tools for data preprocessing, model evaluation, and hyper-parameter tuning. In this chapter, we will learn about the core components and utilities of Scikit-Learn, and how to use them to solve various machine learning tasks.

This chapter is organized as follows. Section 3.1 describes the main features ...