Lecture Notes

January 9
                     Lecture 1: Introduction
                     Lecture 2: Introduction to ML, linear algebra

January 12
                     Finish Lecture 2
                     Matlab Primer

January 16
                     Finish intro to Matlab
                     Lecture 3: Nearest Neighbor Classifier

January 19
                     Lecture 4: Linear Classifier

January 23
                     Continue Lecture 4

January 26
                     Lecture 5: Boosting

January 30
                     Finish Lecture 5 and
                     Lecture 6: Neural Networks

February 2
                     Continue Lecture 6

February 6
                     Finish Lecture 6 and
                     Lecture 7: Cross Validation

February 9
                     Quiz 1

February 13
                     Lecture 8: Introduction to Natural Language Processing and
                     Lecture 9: Language Models

February 16
                     Lecture 9

February 27
                     Finish Lecture 9 and
                     Lecture 10: POS tagging

March 1
                     Finish Lecture 10

March 5
                     Lecture 11: Information Retrieval

March 8
                     Finish Lecture 11

March 12
                     Lecture 12: CV: Filtering

March 15
                     Quiz 2

March 19
                     Lecture 13: CV: Edge Detection and
                     Lecture 14: CV: Stereo

March 15
                     Continue Lecture 14

March 26
                     Finish Lecture 14 and                     
                     Lecture 15: CV: Segmentation

March 29
                     Continue Lecture 15

April 2
                     Finish Lecture 15 and                     
                     Lecture 16: CV: Motion

April 5
                     Finish Lecture 16

April 9
                     Quiz 3, from 10:30 to 11:30