https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/ 2026-05-11T17:26:57+00:00 https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/ https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/_media/wiki:dokuwiki-128.png text/html 2019-10-25T16:14:48+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/assignment?rev=1572020088&do=diff * [Assignment One] * [Assignment Two] text/html 2012-08-30T18:58:29+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/contact?rev=1346353109&do=diff Contact Course Director * Hui Jiang * Office: CSE 3014 (Computer Science and Engineering Building) * Phone: (416) 736-2100 x. 33346 * Email: hj AT cse DOT yorku DOT ca You may contact the course director by e-mail at any time. Office Hours You may visit the Course Director during the following regularly scheduled office hours: text/html 2016-09-12T21:11:02+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/course_outline?rev=1473714662&do=diff Course Outline The course outline is a guideline to topics that will be discussed in the course, and when they will be discussed: Weeks 1 and 2 Machine Learning (basic concepts) Math Background: probabilities; Bayes theorem; statistics; estimation; regression; hypothesis testing; entropy; mutual information; decision tree; optimization theory and convex optimization; matrix decomposition text/html 2007-08-01T14:34:50+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/faq?rev=1185978890&do=diff Frequently Asked Questions Here, you can list frequently asked questions from your students along with responses. General Do I need to register for a CSE Computer Account? Yes. Do I need to attend class? If you wish to pass. Tests Do I need to write all tests? text/html 2007-08-02T17:22:57+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/forums?rev=1186075377&do=diff Forums This page acts as a future placeholder for a link to a forum system. text/html 2019-11-18T21:43:10+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/grades?rev=1574113390&do=diff Grades The weight distribution of the course components is as follows: * Two Assignments (25% 30%): basic concepts, principles, algorithms (A1: 10%; A2: 20%) * Two lab projects (50% 70%): project one (20% 30%); project two + presentation (30% text/html 2019-12-13T15:59:59+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/important_dates?rev=1576252799&do=diff Important Dates Here, Important dates for this course: * Dec 18 Jan 5: project2 report is due * Dec 13 and 16: 2-5pm project2 presentation (location TBA) * Dec 4: 2-5pm final exam (Location: BRG 217) * Dec 4: A2 is due * Nov 18: last lecture text/html 2019-11-13T16:42:58+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/lecture_notes?rev=1573663378&do=diff * Weeks 1-2: A. [Machine Learning (basic concepts)]; B. [Math foundation]: probabilities and statistics, Bayes theorem, Entropy, mutual information, decision tree, optimization, matrix factorization (Weekly Reading: W2) (A useful online manual on Matrix Calculus) * Week 3: [Feature Extraction in Machine Learning]: PCA, LDA, manifold learning (MDS, SNE, LLE, Isomap), data virtualization. (Weakly reading: text/html 2007-07-31T18:55:53+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/policies?rev=1185908153&do=diff Policies Here, you can list specific course policies. Academic Dishonesty For more information on Academic Dishonesty, click here. text/html 2019-08-22T21:14:28+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/presentations?rev=1566508468&do=diff Advanced Topics for self-study and Presentation text/html 2019-12-04T20:10:49+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/projects?rev=1575490249&do=diff * [Project one] * Project Two: Your project 2 report will be submitted as a CS conference paper. You may use any latex temple from CVPR, ACL, ICML, etc. It is expected to be 6-8 pages (double-columned). I will mark your report as a conference reviewer based on format, writing style, work quality, extra additions to the existing methods, etc.. text/html 2007-07-31T18:59:29+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/resources?rev=1185908369&do=diff Resources Use this page to list additional Resources that may be helpful to your students. * Department of CSE Home Page * York Exam Schedule text/html 2024-03-08T13:45:35+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/sidebar?rev=1709905535&do=diff * What's New * Course Outline * Lecture Notes * Important Dates * Assignments * Projects * Grades * Textbook * Contact text/html 2019-09-04T16:12:26+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/start?rev=1567613546&do=diff EECS 6327 Probabilistic Models & Machine Learning (Fall 2019) Description The course introduces some probabilistic models and machine learning methods. The covered topics may include: * Bayesian Decision theory, Generative vs Discriminative modelling text/html 2016-08-29T19:28:31+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/textbook?rev=1472498911&do=diff Textbook There is no required textbook for this course. Three optional reference books: * C. M. Bishop, Pattern Recognition and Machine Learning, Springer, ISBN 0-387-31073-8. * R. O. Duda, P. Hart and D. Stork, Pattern Classification (2nd Edition), John Wiley & Sons, Inc., ISBN 0-471-05669-3. text/html 2019-12-13T16:04:26+00:00 Anonymous (anonymous@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2019-20/F/6327/whats_new?rev=1576253066&do=diff What's New? Refresh your page!!! * Dec 13: To give you more time to work on project2. The deadline for the project2 report is extended to Jan 5 (midnight). Note that this is a hard deadline and no further extension is possible. * Dec 13: Both BRG211 and LAS3033 have nice A/V equipments installed. No matter whether you use your own laptop, your USB drive or any online drive, please go there before 1:50 to make sure it works fine. We will start at 2pm SHARP.