Machine Learning Course for Beginners

A comprehensive machine learning course covering both theory and practical applications, including supervised learning, unsupervised learning, and ensemble techniques like bagging and boosting. It features decision trees, k-means clustering, and advanced algorithms such as XGBoost. The course emphasizes hands-on projects, data exploration, and evaluation metrics for effective model building.