Machine Learning - Monsoon 2019

Instructor Saket Anand 
 Lecture Time and Venue Mon, Thu - 02:30PM - 04:00PM; Venue - C11
 Office HoursSaket: Mon - 01:00PM-02:00PM, B-410 or by appointment
 TALokender Tiwari (Head TA), Shagun Uppal, Deepak Magesh Srivastava and William Scott Paka
 TA Office HoursLokender: Tuesdays, 3-4PM, Venue: B-413
Shagun: Thursdays, 4-5PM, Venue: A-519
Deepak: Wednesdays, 4-5PM, Venue: Ground Floor@Library 
William: Fridays, 1-2PM, Venue: A-519
(or by appointment)
 Course Group Use Google Classroom (registration code: jtew2n) for discussions.
 HW Submission  Google Classroom (registration code: jtew2n)
 Prerequisites Linear Algebra
 Probability and Statistics
 Advanced Calculus (Vector Differentiation)
 Programming (Python)
 TextbooksReading material will be assigned from different texts along with lecture notes. 
 
Reference Books:
  1. [SS] Understanding Machine Learning: From Theory to Algorithms. Shai Shalev-Shwartz and Shai Ben-David. Cambridge University Press, 2014.
  2. [TM] Machine Learning. Tom M. Mitchell. McGraw Hill, 1997.
  3. [CB] Pattern Recognition and Machine Learning. Christopher M. Bishop. Springer, 2006.
  4. [DHS] Pattern Classification. Richard Duda, Peter Hart and David Stork. Second Ed., Wiley 2006.
The reading material from these books will be referred using the following abbreviation: Chapter 2.3.1 from Bishop's text as [CB-Ch-2.3.1]; Appendix C from Bishop's text as [CB-App-C], and so on.

IIIT-Delhi students can also find these texts here.
 Relevant Journals and Conferences Journals
 JMLRIEEE TPAMIIEEE Trans. on Neural Networks and Learning Systems, Machine Learning
 Conferences:
 NeurIPS, ICML, KDD. Often papers in CVPR, ICCV, AAAI, IJCAI, etc. are also relevant
 Early Submission Policy Most, if not all, assignments will have online submissions, typically at 11:59PM on the assigned date. If you submit your assignment more than 6 hours before the deadline, you will get 5% bonus on that assignment.
 Late Submission PolicyThe deadlines will be hard. Please prepare to submit a couple of hours before the deadline. Network connection problems, hard drive crashing, blue screen of death, and similar reasons will not be honored for missing the deadline. 
 

You have three days of extension which can be used any time over the semester. The quantum of extension will be one day. There will be no additional extensions whatsoever on grounds of medical emergency etc. 

For project related deadlines, there will be no extensions.  

Late submission would automatically use up one extension day. If none remain, then a zero will be assigned for that submission.
 Graded Sheet Collection  Policy TAs will announce the date and time of collection on backpack. 
 If you are unable to collect your sheet on the specified day, you have the following options. 
1. Request a friend to collect your sheet and inform the TA by email. Without your email, the answer sheet cannot be handed over to your friend. 
2. Within one week of the announced date, you (or your friend) may collect your answer sheets during the TA's office hours (or by appointment). 
3. In case of any discrepancy in grading, you must take the issue up within one week of the announced date. No requests will be entertained after this one week period. 
 Doubt Resolution PolicyFor resolving doubts about concepts, assignments, etc., please visit Instructor/TA during their office hours or with prior appointment (by email). 
Use backpack extensively to resolve doubts regarding assignments. The TAs/Instructors will be responsive on backpack. 
Note: Please make sure you ask your doubts on Backpack about Assignments at least 2 days before the submission deadline. The TAs will not be held responsible for not answering your queries in the last two days before the deadline.  
Another Note: While Anonymous access is provided to encourage discussion/doubt resolution without inhibitions, please make sure that you are respectful towards others. The anonymous discussion privileges will be removed at the first instance of abuse (decided by the instructor). 
 Plagiarism Policy  Every submission (written and code) will be run through a plagiarism checker. IIITD's academic dishonesty policy will be enforced. 
Course Description Course Description contains the prerequisites, post conditions, weekly plan and other information.  
 Auditing RequirementsStudents need to submit all assignments and projects on time and achieve a grade of at least the class average. Audit students are not permitted to do projects with registered students. Quiz and Exams are optional.