Introduction to Machine Learning with Python

A Guide for Data Scientists

by Andreas C. Müller, Sarah Guido

Practical approaches to solving machine learning problems with Python using scikit-learn.

Preface

1. Introduction

2. Supervised Learning

3. Unsupervised Learning and Preprocessing

4. Representing Data and Engineering Features

5. Model Evaluation and Improvement

6. Algorithm Chains and Pipelines

7. Working with Text Data

8. Wrapping Up