Lecture Notes

January 6
                     Lecture 1: Introduction
                     Lecture 2: Introduction to ML, linear algebra

January 9
                     Intro to Matlab
                     Matlab Primer

January 12
                     Lecture 3: Nearest Neighbor Classifier

January 15
                     Lecture 4: Linear Classifier

January 19
                     Continue Lecture 4

January 22
                     Lecture starts at 8:30
                     Lecture 5: Boosting

January 26
                     Lecture 6: Neural Networks

January 29
                     Lecture starts at 8:30
                     Finish Lecture 6 and
                     Lecture 7: Cross Validation

February 2
                     Lecture 8: Introduction to Natural Language Processing and
                     Lecture 9: Language Models

February 5
                     QUIZ 1

February 9
                     Finish Lecture 9

February 12
                     Lecture 10: Spelling Correction

February 23
                     Lecture 11: POS tagging

February 26
                     Finish Lecture 11 and start
                     Lecture 12: Information Retrieval

March 2
                     Finish lecture 12

March 5
                     Lecture 13: CV: Filtering

March 9
                     Finish Lecture 13 and
                     Lecture 14: CV: Edge Detection

March 12
                     Finish Lecture 14

March 16
                     NO LECTURE

March 19
                     Quiz 2

March 23
                     Lecture 15: CV: Segmentation

March 26
                     Continue Lecture 15

March 30
                     Finish Lecture 15 and
                     Lecture 16: CV: Stereo

April 2
                     Finish Lecture 16

April 6
                     QUIZ 3 from 9:30-10:30