Data Science with Python

Chapter 3

Introduction to Machine Learning via Scikit-Learn

Learning Objectives

By the end of this chapter, you will be able to:

• Prepare data for different types of supervised learning models.
• Tune model hyperparameters using a grid search.
• Extract feature importance from a tuned model.
• Evaluate performance of classification and regression models.

In this chapter, we will be covering the important concepts of handling data and making the data ready for analysis.

Introduction

scikit-learn is a free, open source library built for Python that contains an assortment of supervised and unsupervised machine learning algorithms. Additionally, scikit-learn provides functions for data preprocessing, hyperparameter tuning, and model evaluation, ...