Covers feature extraction, clustering, and classification methods for high-dimensional datasets and behavioral analysis using PCA, t-SNE, k-means, GMM, and various classification algorithms.
Explores logistic regression fundamentals, including cost functions, regularization, and classification boundaries, with practical examples using scikit-learn.