Singular Value DecompositionExplores Singular Value Decomposition and its role in unsupervised learning and dimensionality reduction, emphasizing its properties and applications.
Clustering: Theory and PracticeCovers the theory and practice of clustering algorithms, including PCA, K-means, Fisher LDA, spectral clustering, and dimensionality reduction.
Linear Dimensionality ReductionExplores linear dimensionality reduction through PCA, variance maximization, and real-world applications like medical data analysis.
Data Science EssentialsCovers the essentials of data science, including data handling, visualization, and analysis, emphasizing practical skills and active engagement.
