Chapter 1, Machine Learning Basics, provides an introduction to machine learning as well as what we hope to accomplish in this book.
Chapter 2, ReflectInsight – Real-Time Monitoring, introduces ReflectInsight, a powerful, flexible, and rich framework that we will use throughout the book for logging and insight into our algorithms.
Chapter 3, Bayes Intuition – Solving the Hit and Run Mystery and Performing Data Analysis, exposes the reader to Bayes intuition. We will also examine and solve the famous "hit and run" problem, where we try to determine who fled the scene of an accident.
Chapter 4, Risk versus Reward – Reinforcement Learning, shows how reinforcement learning works.
Chapter 5, Fuzzy Logic – Navigating the ...