Introduction

Most businesses possess a wealth of data on their operations and customers. Reporting on this data in the form of descriptive charts, graphs, and tables is a good way to understand the current state of the business. However, in order to provide quantitative guidance on future business strategies and operations, it is necessary to go a step further. This is where the practices of machine learning and predictive modeling are needed. In this book, we will show how to go from descriptive analyses to concrete guidance for future operations, using predictive models.

To accomplish this goal, we'll introduce some of the most widely used machine learning tools via Python and many of its packages. You will also get a sense of the practical skills necessary to execute successful projects: inquisitiveness when examining data and communication with the client. Time spent looking in detail at a dataset and critically examining whether it accurately meets its intended purpose...