M0. Welcome to Introduction to Machine Learning
M1. Machine Learning Terminology
M2. Decision Trees
M3. Splitting, Cross-Validation and the Fundamental Tradeoff
M4.Similarity-Based Approaches to Supervised Learning
M5. Preprocessing Numerical Features, Pipelines and Hyperparameter Optimization
M6. Preprocessing Categorical Variables
M7. Assessment and Measurements
M8. Linear Models
Module Closing Remarks
- 0. Congratulations!

2.1. Exercises

Supervised vs. Unsupervised Learning

Given the following scenarios, would each example be considered supervised learning or unsupervised learning?

2. Types of Machine Learning

3. Classification vs. Regression