Lesson 1: K-Means Clustering
- Basics of K-Means Clustering
- Choosing Number of Clusters
- Applications and Limitations
Lesson 2: Hierarchical Clustering
- Introduction to Hierarchical Clustering
- Agglomerative vs. Divisive
- Dendrograms and Cutting Strategies
Lesson 3: Principal Component Analysis (PCA)
- Basics of PCA
- Dimensionality Reduction
- Applications of PCA
Lesson 4: Anomaly Detection
- Introduction to Anomaly Detection
- Techniques and Algorithms
- Applications