John Schrom is an Epidemiologist by training, a Data Scientist by occupation (at Practice Fusion), and a PhD student by hobby. His interests primarily revolve around finding utility in social data, the application and representation of health data, and general data mining and machine learning techniques.

As storage and collection technology has become cheaper and more precise, companies and individuals are eager to extract relevant information from large data sets. This book focuses on the tools of machine learning and statistics in a practical manner, with lots of case studies specific to the challenges of working with healthcare data. By exploring each problem in depth, you'll build your intuitive understanding of machine learning without requiring a strong background in advanced mathematics. You'll be able to recognize when your problems match traditional problems closely, and apply classical tools from statistics to your problems, while working within the legal bounds of the US healthcare system.