Month 4: Unsupervised Learning Techniques

Week 1: Clustering

• Introduction to Clustering
• K-Means Clustering
• Hierarchical Clustering
• Density-Based Clustering
• Clustering Evaluation

Week 2: Dimensionality Reduction

• Introduction to Dimensionality Reduction
• Principal Component Analysis (PCA)
• Singular Value Decomposition (SVD)
• Linear Discriminant Analysis (LDA)
• Applications of Dimensionality Reduction

Week 3: Independent Component Analysis (ICA)

• Introduction to ICA
• ICA for Blind Source Separation
• Applications of ICA
• Comparison with PCA

Week 4: t-SNE

• Introduction to t-SNE
• Dimensionality Reduction with t-SNE
• t-SNE vs PCA
• Applications of t-SNE