Table of Contents
- Thinking in Machine Learning
- Tools Overview
- Turning data into information
- Models: Learning from information
- Linear Models
- Neural nets
- Features: How algorithms see the world
- Learning with ensembles
- Some real world examples

Key design strategies to create intelligent systems