Lecture Schedule

Apr 2 No lecture.
Apr 4 Administrivia and Course Overview. Slides
Apr 9 A Geometric View of Linear Algebra. Notes
Apr 11 Nearest Neighbor Classification. Notes
Apr 16 Nearest Neighbor Classification. See Notes for 4/11 lecture. Examples Slides
Apr 18 Decision Trees. Notes
Apr 23 Decision Trees. See Notes for 4/18 lecture.
Apr 25 Decision Trees. Practice Problem Set 1. See Notes for 4/18 lecture. Notes 1 Notes 2
Apr 30 Linear Classification and Perceptron. Notes
May 2 Perceptron. See Notes for 4/30 lecture.
May 7 Midterm
May 9 Midterm Solutions Discussion. Perceptron. See Notes for 4/30 lecture. Notes 1
May 14 Kernels. Notes
May 16 Kernels. See Notes for 5/14 lecture.
May 21 Finish up with Kernels. Bias and Variance. Notes
May 23 Bias and Variance. Ensemble Learning. See Notes for 5/21. Notes
May 28 Boosting. See Notes for 5/23.
May 30 Viola and Jones. Practical Tips for ML. Slides 1 Slides 2
Jun 4 k-means Notes