Lecture Notes

January 4
                     Lecture 1: Introduction
                     Lecture 2: Introduction to ML, linear algebra

January 7
                     Intro to Matlab
                     Matlab Primer

January 11
                     Lecture 3: Nearest Neighbor Classifier

January 14
                     Lecture 4: Linear Classifier

January 18
                     Continue Lecture 4

January 21
                     Lecture starts at 8:30
                     Lecture 5: Boosting

January 25
                     Lecture 6: Neural Networks

January 28
                     Lecture starts at 8:30
                     Finish Lecture 6 and
                     Lecture 7: Cross Validation

February 2
                     Finish Lecture 7 and
                     Lecture 8: CV: Intro and Filtering

February 5
                     Finish Lecture 8 and
                     Lecture 9: CV: Edge Detection

February 8
                     NO LECTURE

February 11
                     Quiz 1

February 22
                     Finish Lecture 9 and

February 25
                    
                     Lecture 10: CV: Segmentation

February 29
                     Finish lecture 10

March 3
                     Lecture 11: CV: Stereo

March 7
                     Finish lecture 11 and
                     Lecture 12: CV: Convolutional Neural Networks

March 10
                     Lecture 13: Introduction to Natural Language Processing and
                     Lecture 14: Language Models

March 14
                     Finish Lecture 14

March 17
                     Quiz 2

March 21
                     Finish Lecture 14
                     Lecture 15: Spelling Correction

March 23
                     Finish Lecture 15

March 28
                     Lecture 16: POS tagging

March 31
                     Finish lecture 10 and
                     Lecture 17: Information Retrieval

April 4
                     QUIZ 3 from 9:30-10:30