Chapter 1:Machine Learning Basics

Chapter 2: ReflectInsight – Real-Time Monitoring

Chapter 3:Bayes Intuition – Solving the Hit and Run Mystery and Performing Data Analysis

Chapter 4: Risk versus Reward – Reinforcement Learning

Chapter 5: Fuzzy Logic – Navigating the Obstacle Course

Chapter 6: Color Blending – Self-Organizing Maps and Elastic Neural Networks

Chapter 7: Facial and Motion Detection – Imaging Filters

Chapter 8: Encyclopedias and Neurons – Traveling Salesman Problem

Chapter 9: Should I Take the Job – Decision Trees in Action

Chapter 10: Deep Belief – Deep Networks and Dreaming

Chapter 11: Microbenchmarking and Activation Functions

Chapter 12: Intuitive Deep Learning in C# .NET

Chapter 13: Quantum Computing – The Future