Lesson 1: Linear Regression
- Basics of Linear Regression
- Model Fitting and Evaluation
- Applications and Limitations
Lesson 2: Logistic Regression
- Basics of Logistic Regression
- Binary Classification
- Evaluation Metrics
Lesson 3: Decision Trees
- Introduction to Decision Trees
- Building and Evaluating Decision Trees
- Pruning and Optimization
Lesson 4: Ensemble Methods
- Basics of Ensemble Methods
- Bagging and Boosting
- Random Forests and Gradient Boosting