Machine Learning Algorithms

This course introduces statistical machine learning, covering key concepts and algorithmic foundations.
Core Topics: Includes dimensionality reduction, overfitting, ensemble learning, and evaluation techniques.
Algorithms: Covers clustering (K-Means), classification (SVM, Decision Trees, Neural Networks), and regression (Linear & Logistic Regression).
Implementation: Students will perform theoretical derivations, computations, and algorithm development from scratch.
Final Project: A hands-on project where students apply learned techniques to a real-world problem.
This course provides a strong foundation in machine learning model design, optimization, and evaluation for practical applications.