Machine Learning Basics

This book is a "plain-speak" introduction to Machine Learning. It introduces the concepts of unsupervised learning and supervised learning and explains how they differ. It covers clustering methods (K-means, Hierarchical), the Nearest Neighbors algorithm, Decision Trees, Linear Regression, Probabilistic Classification, and Reinforcement Learning.