Applied Machine Learning

3 credits

Topics include regression (linear regression with multiple features, nearest neighbors and kernel regression, ridge regression and lasso), classification (linear classifiers, logistic regression, decision trees, boosting), clustering, dimensionality reduction, overfitting & regularization, feature selection, and performance evaluation. Implementation of these concepts in practical applications is the primary focus of this course.