Lecture Schedule

Mar 30 Course Overview Slides
Apr 1 A Geometric View of Linear Algebra. Notes
Apr 3 A Geometric View of Linear Algebra. See Notes for 4/1 lecture.
Apr 6 Nearest Neighbor Classification. Notes
Apr 8 Nearest Neighbors See 4/6.
Apr 10 Nearest Neighbors See 4/6.
Apr 13 Decision Trees Notes
Apr 15 Decision Trees. See 4/13.
Apr 17 Decision Trees. See 4/13.
Apr 20 Decision Trees. See 4/13.
Apr 22 Decision Trees. See 4/13.
Apr 24 Decision Trees. See 4/13.
Apr 27 Linear Classification. Notes
Apr 29 Linear Classification. See 4/27.
May 1 Perceptron. See 4/27.
May 4 Perceptron. See 4/27.
May 6 Midterm
May 8 Finish up Linear Classification. Notes
May 11 Kernels. Notes
May 13 Kernels. Midterm Solutions Discussion.
May 15 Kernels. See 5/11 notes.
May 18 Kernels. See 5/11 notes.
May 20 Kernels Problem Session.
May 22 Bias and Variance. Bias and Variance Notes
May 27 Ensemble Learning. Notes
May 29 Boosting. See 5/27.
Jun 1 Finish up Boosting. Viola and Jones. Slides
Jun 3 Tips for Practical ML. Slides
Jun 5 Problem Session.