Machine Learning - Classification

This course teaches classification, one of the most widely used techniques in machine learning, with a broad array of applications, including risk assessment, ad targeting, medical diagnosis, and spam detection. Students will learn important algorithms used in classification by focusing on the core techniques, which are widely used in the real world to get state-of-the-art performance. This course will cover algorithms including Decision Trees, K nearest neighbors, Naïve Bayes, Logistic Regression, and relevant metrics (Accuracy, Recall, Precision, F1 Score). Students will gain practical experience with these approaches by developing their own models for solving real-world problems.