CS 6140

Machine learning

Spring 2017

Tuesdays 11:45 - 1:25am, Robinson Hall 109

Thursdays 2:50 - 4:30pm, Robinson Hall 109

Instructor: Olga Vitek

Email: o.vitek@neu.edu

Office hours: WVH 310F, Tuesdays 1:30-2:30pm or by appointment.

Phone: (617) 373-6305

Mailbox: WVH 202


Teaching assistant: Sara Taheri

Email: mohammadtaheri.s@husky.neu.edu

Office hours: WVH 310, Tuesdays 10:00-11:00am or by appointment.


Admin: Syllabus, Piazza, Blackboard. Academic integrity.


Required texts:

    [KM] Machine Learning: A Probabilistic Perspective. Kevin P. Murphy, MIT Press 2012.

    [HTF] Elements of Statistical Learning. T. Hastie, R. Tibshirani and J. Friedman, Springer, 2009.

    [JWHT] An Introduction to Statistical Learning. G. James, D. Witten, T. Hastie, R. Tibshirani,

                Springer 2013

Optional texts:

    Pattern Classification, 2nd Edition. R. O. Duda, P. E. Hart, D. Stork, Wiley and Sons, 2001.

    Pattern Recognition and Machine Learning. C. M. Bishop, Springer 2006.

    Machine Learning. T. Mitchell, McGraw-Hill, 1997.


1. Introduction.

KM ch1. HTF ch2.1-2.3.

Tue, Jan 10:


2. Probability review.

KM ch2.

Thu, Jan 12: Hw1 out.

Tue, Jan 17:


3. Linear regression. Model assessment and selection.

KM ch7. HTF ch3.1-3.3.

KM ch13. HTF ch3.4-3.9, ch18.

Thu, Jan 19:.

Tue, Jan 24: Hw1 due.


Thu, Jan 26: no class Hw2 out.

Tue, Jan 31: no class

Thu, Feb 2:


5. Logistic regression.

KM ch8. HTF ch4.4.

Tue, Feb 7:

Thu, Feb 9: Hw2 due. Project group due. Class cancelled, snow day.

Tue, Feb 14: Hw3 out.


6. Generative classifiers.

Thu, Feb 16:

Tue, Feb 21:

Thu, Feb 23:

Feb 24: Hw3 due.


7. Splines and kernels. Support vector machines.

KM ch14. HTF ch12.

Tue, Feb 28: Midterm.

Thu, Mar 2:


Tue, Mar 7: Spring break.

Thu, Mar 9: Spring break.


Tue, Mar 14: Project proposal due. Class cancelled, snow day.

Thu, Mar 16:

Tue, Mar 21:


8. Tree-based and ensemble methods.

KM ch16. HTF ch9.2, ch10, ch15-16.

Thu, Mar 23:

Tue, Mar 28:

Thu, Mar 30:

Saturday, April 1. Hw 4 out.


9. Neural networks, deep learning.

KM ch16.5. HTF ch11.

Tue, Apr 4:

Thu, Apr 6:

Tue, Apr 11: Project report due.

Thu, Apr 13: No class. See Piazza for instructions.


Tue, Apr 18: Hw 4 due. Project review due. Optional in-class review time.

Thu, Apr 20: Final exam.

Tentative schedule and handouts