Course Descriptions

Course Synopsis/Sample Syllabi: output_f81d2.pdf

Prerequisites: 16:958:563. Supervised and unsupervised learning; shrinkage and regularization in regression; splines and kernel smoothing; linear discriminant analysis, logistic regression, supper vector machines and regularization in classification;  model assessment, model selection and cross-validation; tree based methods and boosting; introduction to neural networks; introduction to text mining. Emphasis on the use of data mining techniques in finance.