Introduction

Contents:

  - Introduction to Machine Learning
  - Math Primer
  - Classification
  - Regression
  - Regularization
  - Trees and Forests
  - Deep Learning
  - Reinforcement Learning
  - Learning Pipelines
  - Data Preparation
  - Feature Engineering
  - Evaluating Models
  - Observing Models