Apr 1 
Course Overview 
Slides 
Apr 3 
A Geometric View of Linear Algebra. 
Notes

Apr 8 
Finish up A Geometric View of Linear Algebra. 
See Notes for 4/3 lecture. 
Apr 10 
Nearest Neighbor Classification. 
Notes

Apr 15 
More on Nearest Neighbor Classification. 
See Notes for 4/10 lecture. 
Apr 17 
Decision Trees. 
Notes 
Apr 22 
Decision Trees. 
See Notes for 4/17 lecture. 
Apr 24 
Finish up Decision Trees. 
See Notes for 4/17 lecture. Notes 1
Notes 2 
Apr 29 
Decision Tree Example. Linear Classification and Perceptron. 
Notes 
May 1 
Perceptron. 
See Notes for 4/29 lecture. 
May 6 
Midterm 

May 8 
Midterm Solutions Discussion. Perceptron. 
See Notes for 4/29 lecture. 
May 13 
Voted and Averaged Perceptron . 
See Notes for 4/29 lecture. 
May 15 
Finish up Linear Classification. Kernels. 
Linear Classification Notes Kernels Notes 
May 20 
Kernels. 
See 4/15 notes. 
May 22 
Finish up Kernels. Start with Bias and Variance. 
Bias and Variance Notes 
May 27 
Kernels Problem Session. 

May 29 
Ensemble Learning. 
Notes 
Jun 2 
Finish up Boosting. Viola and Jones. 
Slides 
Jun 4 
Tips for Practical ML. 
Slides 