Module 4: Supervised Learning Techniques
- Linear Regression
- Logistic Regression
- Classification models
- Assumptions
- Evaluation metrics
- Hyperparameter tuning
Module 5: Unsupervised & Ensemble Learning
- K-Means, Hierarchical clustering
- Dimensionality reduction
- Bagging & Boosting
- Random Forest & other ensembles
