MA 751 Supplementary materials

 

Course Announcement -    

Announcement

Course information and notes – 

Syllabus

Notes on matrix notation

Problem set 1

Suggestions, problem set 1

Problem set 2

Suggestions, problem set 2

Problem set 3

Suggestions, problem set 3

Problem set 4

Suggestions, problem set 4

Problem set 5

Suggestions, problem set 5

Data assignment 1

Problem set 6

Suggestions, problem set 6

Problem set 7

Suggestions, problem set 7

Data assignment 2 (Due Tuesday, March 26)

Problem set 8

Suggestions, problem set 8

Note on Bayesian statistics (Section 8.3)

Problem set 9 (Data Assignment 3)

Suggestions, problem set 9

Problem set 10

Suggestions, problem set 10

Problem set 11

Suggestions, problem set 11

      Vert movie 1;  Vert movie 2

       (Note the first movie shows how Gaussian kernel width affects SVM classification - kernel width narrows with time.

                        Second shows how changing the margin parameter C affects the classification – margin narrows with time)

     Aharoni nonlinear SVM video

Problem set 12

Suggestions, problem set 12

Problem set 13

Suggestions, problem set 13

 

Optional additional material and examples

1.  More on Boosting

2. Decision trees and random forests

3. Details of random forests

 

Lecture Notes -  

1.  The three pillars of machine learning

2. Probability and Measure Theory

3.  Linear Algebra Primer

4.  Inner Products

5.  Statistical machine learning and infinite dimensions

6.  Measure spaces and Hilbert spaces

7.  Reproducing kernel Hilbert Spaces

8.  Support vector machines (SVM) (optional)

9.  Solving SVM (optional)

 

Optional additional material and examples

 

Resources –

Wavelets: older review

Park and Sandberg paper

Park and Sandberg notes

Cucker and Smale

Poggio article