This document provides an introduction to machine learning concepts including: - Machine learning involves learning parameters of probabilistic models from data. - Maximum likelihood and maximum a posteriori estimation are common techniques for learning parameters. - Inductive learning involves constructing a hypothesis from examples to generalize the target function to new examples. Cross-validation is used to evaluate hypotheses on held-out data and avoid overfitting.