- Instructor: Kaveh Kavousi (kkavousi at ut.ac.ir) and Hesam Montazeri (hesam.montazeri at ut.ac.ir)
- Teaching Assistants: Fahimeh Palizban (fahimehpalizban at ut.ac.ir) & Zohreh Toghrayee ( zohreh.toghrayee at ut.ac.ir)
- Time & Location: Sep-Dec 2019, lectures are held on Sundays 15:00-17:00 and Tuesdays 13:00-15:00 at Ghods st. 37, Department of Bioinformatics, IBB, Tehran.
- Google Calendar: for the detailed schedule, add the course calendar to your calendars!
- The Elements of Statistical Learning by Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie [ESL]
- An Introduction to Statistical Learning: With Applications in R by Daniela Witten, Gareth James, Robert Tibshirani, and Trevor Hastie [ISL]
- Pattern Recognition and Machine Learning by Christopher Bishop. [PRML]
- A First Course in Machine Learning by Simon Rogers and Mark Girolami [FCML]
[CS229] CS229 Lecture notes at Stanford available at here
- Final exam, 22/10/1398
| Week | Lecture | Reading Assignments | Homeworks & Projects | By |
|---|---|---|---|---|
| W1 | Logistics (slides) (31/6/1398) Lecture 1- Introduction to machine learning; simple linear regression- gradient descent algorithm (slides; whiteboard notes) (2/7/1398) Lecture 2- linear regression- analytical solution; mathematical formulation in matrix form (whiteboard notes) Tutorial 1- Introduction to R (slides) |
Required: FCML, Sec. 1.1-3 CS229, Supervised learning (notes) Highly recommended: Linear algebra review from Stanford (notes) |
HW1 | HM |