Practice Sessions Practice 01 - Feb 15 - Naive Bayes Slides (PDF) Practice 02 - Feb 22 - Basic linear classifier & Perceptron Practice 03 - March 1 - F1 measure & ROC & Feature engineering ROC explanation Feature engineering example Practice 04 - March 8 - Linear regression Practice 05 - March 15 - Perceptron in dual form & SVM Exercises (PDF) Practice 06 - March 29 - Kernel methods Practice 07 - April 05 - Decision trees Exercises (PDF) Practice 08 - April 12 - Logistic regression Exercises (PDF) Practice 09 - April 19 - Backpropagation & Softmax Exercises (PDF) Practice 10 - May 10 - Ensemble methods Exercises (PDF) Practice 11 - May 17 - Probabilistic graphical models Exercises (PDF) Slides (PDF) Practice 12 - May 24 - HMM & Gaussian Processes (discussing HW6) Sampling example code (not commented)
