Calculus [Online course from MIT]
Linear Algebra [CS6015 or equivalent] | [Online course from MIT]
Probability Theory [CS6015 or equivalent] | [Online course from MIT]
Non-linear Optimization [CS5020 or equivalent] | [First Course in Optimization by Prof. Soman (IITB) available on CDEEP]
Pattern Recognition and Machine Learning [CS5691 or equivalent] | [Andrew Ng's ML course]
Deep Learning [CS7015 or equivalent]
Instructor: Mitesh M. Khapra
When: Jan-May 2019
Lectures: Slot K
Where: CS24, CS Building, First Floor
Teaching Assistant
| Name | Lab | Working hours | Days | |
|---|---|---|---|---|
| Preksha Nema | RISE Lab | preksha.nema9@gmail.com | 2-4 pm | Wed,Fri |
| Lecture | Contents | Papers/Slides | Blogs |
|---|---|---|---|
| Lecture 0 | Course Overview | S | - |
| Lecture 1 | Overview of Word Embeddings | S | - |
| Lecture 2 | ELMo | P | - |
| Lecture 3 | Attention Is All You Need | P | B |
| Lecture 4 | BERT | P | - |
| Lecture 5 | What Bert Learns ? | P | - |
| Lecture 6 | XL Net | P | B |
| Lecture 7 | Eernie | P | B |
| Lecture 8 | QA - Datasets | Survey | - |
| Lecture 9 | QA - Overview | S1 | - |
| Lecture 10 | QA - CharEmbedding/CoAttention | S1 | S2 | BiDAF | DCN | QANet Paper | QANet Slides |
| Lecture 11 | QA - SingleFramework | S1 | - |
| Lecture 12 | Overview of Object Detection | - | B |
| Lecture 13 | RCNN, Fast RCNN, Faster RCNN | S | P1 | P2 | P3 | B1 | B2 | B3 |
| Lecture 14 | YOLO | S | P1 | P2 | P3 | B |
| Lecture 15 | Retina Net | P | B |
| Lecture 16 | Single Shot Learning | S | B |
| Lecture 17 | Video Datasets Overview | P | B |
| Lecture 18 | Optical Flow | P1 | P2 | B1 | B2 |
| Lecture 19 | Action Recognition | P | B |
| Lecture 20 | Action Recognition (Contd.) | P1 | P2 | B |
| Lecture 21 | Graph Representation Learning | S1 | S2 | - |
| Lecture 22 | Graph Representation Learning (Contd.) | S | - |
| Lecture 23 | Graph Convolutional Networks | P | - |