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CSL341: Fundamentals of Machine Learning
General Information
Instructor: Parag Singla (email: parags AT cse.iitd.ac.in)
Class Timings (Slot B):
- Monday, 9:30am - 10:55am
- Thursday, 9:30am - 10:55am
Venue:WS 101 (Workshop Room 101) Bharti 101
Teaching Assistants
Name | Email |
Abhinav Kumar | cs5090231 AT cse.iitd.ac.in |
Anuj Gupta | agupta AT cse.iitd.ac.in
| Arpit Jain | cs5090236 AT cse.iitd.ac.in |
Happy Mittal | csz138233 AT cse.iitd.ac.in |
Shubham Gupta | cs5090252 AT cse.iitd.ac.in |
Sudhanshu Sekhar | cs5090255 AT cse.iitd.ac.in |
Yamuna Prasad | yprasad AT cse.iitd.ac.in |
Announcements
- [Thu Oct 31]: Assignment 2, New Due Date: Monday Nov 4 (11:50 pm).
- [Mon Sep 30]: Assignment 2 is out! Due Date: Thursday Oct 31 (11:50 pm).
- [Fri Sep 27]: Assignment submission instructions have been updated (See below).
- [Wed Sep 25]: Assignment 1 has been updated. New Due Date: Sunday Sep 29 (11:50 pm).
- [Wed Sep 4]: The venue for the class on Thursday Sep 5 will be Bharti 101 (instead of WS 101).
- [Sat Aug 10]: Assignment 1 is out! Due Date: Sunday Sep 15 (11:50 pm).
- [Wed Jul 31]: The course website is up, finally!
Course Content
Week | Topic | Book Chapters | Supplementary Notes |
1 | Introduction | Duda, Chapter 1 | |
2,3 | Linear and Logistic Regression, Gaussian Discriminant Analysis | Bishop, Chapter 3.1, 4 |
lin-log-reg.pdf, gda.pdf |
4,5 | Support Vector Machines | Bishop, Chapter 7.1 | svm.pdf |
6 | Neural Networks | Mitchell, Chapter 4 |
nnets.pdf
nnets-hw.pdf
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7 | Decision Trees | Mitchell, Chapter 3 |
dtrees.pdf |
8,9 | Naive Bayes, Bayesian Statistics |
Mitchell, Chapter 6 |
nb.pdf,
bayes.pdf
Conjugate Prior
model.pdf |
10,11 | K-Means, Gaussian Mixture Models, EM | |
kmeans.pdf
gmm.pdf
em.pdf |
12 | PCA | |
pca.pdf
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13 | Learning Theory, Model Selection | Mitchell, Chapter 7 |
theory.pdf
model.pdf |
14 | Application of ML to CrowdSourcing and NLP | |
crowd-ml.pdf
nlp-ml.pdf
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Review Material
References
- Pattern Recognition and Machine Learning. Christopher Bishop. First Edition, Springer, 2006.
- Pattern Classification. Richard Duda, Peter Hart and David Stock. Second Edition, Wiley-Interscience, 2000.
- Machine Learning. Tom Mitchell. First Edition, McGraw-Hill, 1997.
Assignment Submission Instructions
- You are free to discuss the problems with other students in the class. You should include the
names of the people you had a significant discussion with in your submission.
- All your solutions should be produced independently without referring to any
discussion notes or the code someone else would have written.
- All the programming should be done in MATLAB.
Include comments for readability.
- Code should be submitted using Sakai Page.
- [Updated October 31, 2013]: Create a separate directory
for each of the questions named by the question number. For instance, for question 1,
all your submissions files (code/graphs/write-up) should be put in the directory named
Q1 (and so on for other questions). Put all the Question sub-directories in a single
top level directory. This directory should be named as "yourentrynumber_firstname_lastname".
For example, if your entry number is "2009anz7535" and your name is "Nilesh Pathak", your
submission directory should be named as "2009anz7535_nilesh_pathak". You should zip your
directory and name the resulting file as "yourentrynumber_firstname_lastname.zip" e.g. in
the above example it will be "2009anz7535_nilesh_pathak.zip". This single zip file should
be submitted online.
- Honor Code: Any cases of copying will be awarded a zero on the assignment. More severe penalties may follow.
- Late Policy: You will lose 20% for each late day in submission. Maximum of 2 days late submissions are allowed.
Assignments
- Assignment 2 New Due Date: 11:50 pm, Monday November 4, 2013.
Datasets:
- Assignment 1. New Due Date: Sunday September 29, 2013.
Project
To know more about the class project, click here.
Grading Policy
Assignments (2) | 16% |
Project | 25% |
Minor I | 12% |
Minor II | 12% |
Major | 35% |
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