Data preparation involves transforming raw data in to a form that can be modeled using machine learning algorithms. Cut through the equations, Greek letters, an

This book is a practical guide to problems that commonly arise when developing a machine learning project. The book's topics are: Exploratory data analysis Data

This book focuses on the importance of clean, well-structured data as the first step to successful data mining. It shows how data should be prepared prior to mi

The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog pr

The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the mode