AI Experience Laboratory
Fall 2023
Schedule: Mon/Wed 4:00pm-6:30pm
Location: GIST College Building A (N4), Room 227 (Zoom Online) / Class Colab
Instructor: Ue-Hwan, Kim (uehwan@gist.ac.kr)
Office: GIST Central Research Facilities (C11) 407
Office Hour: Tue 4pm-5pm or by appointment
TAs:
Ji-Ae, Yoon (jiaeyoon@gm.gist.ac.kr)
Jae-Woo, Kim (kjw01124@gm.gist.ac.kr)
Notice
- Review report format available here
- Recitations start from September 6 :)
- Please give your class feedback through this link by September 27!
- Midterm review will be live online from 5pm to 6pm on Oct. 18 (after recitation)
- [Midterm] Date: Oct. 23, 4pm-6pm / Location: GIST College Building C (N6) Room 104
- The exam is closed book, closed notes, closed computer, and closed calculator
- Just need to bring your pen, pencil and erasers in addition to your student ID card
- Coverage: Session 00 ~ Session 05 (excluding recitations)
- Result released (see schedule)!
- Claim registration due on Oct. 31
- Claim during Nov. 1, 4pm-5pm through Zoom
- Final exam review will be live online from 5pm to 6pm on Dec. 6 (after recitation)
- [Final Exam] Date: Dec. 11, 4pm-6pm / Location: Oryong Hall (W1) Room 101
- The exam is closed book, closed notes, closed computer, and closed calculator
- Just need to bring your pen, pencil and erasers in addition to your student ID card
- Coverage: Session 06 ~ Session 10 (excluding recitations and AI days)
- Result will be out on Dec. 16 (Released!)
- Claim registration due on Dec. 17
- Claim during Dec. 18, 4pm-6pm through Zoom
Introduction
This course will showcase various methods in machine learning and deep learning. Throughout the semester, emphasis will be put on practical use cases. Examples of specific methods this course covers includes convolutional neural networks, recurrent neural networks, transformers and generative adversarial networks. Further, we will use Google Colab as our development environment.
References
- Introduction to Deep Learning @ CMU Link
- Deep Learning @ Eberhard Karls Universität Tübingen Link
- Introduction to Deep Learning @ UW Link
- Deep Learning for Computer Vision @ Stanford Link
- Natural Language Processing with Deep Learning @ Stanford Link
- Learn PyTorch for Deep Learning @ ZTM Link
- Deep Learning from Scratch Link
- Dive into Deep Learning (Aston Zhang et al., 2019) Link
Schedule
| Date | Topic | Materials | Recitations |
|---|---|---|---|
| 08-28 | [Session 00.0] Introduction | Lecture Slides Submit Result | |
| 08-30 | [Session 01.0] Preliminary | Lecture Slides Submit Result | |
| 09-04 | [Session 01.1] Preliminary (cont'd) | Lecture Slides Submit Result | |
| 09-06 | [Session 02.0] Perceptrons | Lecture Slides Submit Result | Exercises Solution |
| 09-11 | [Session 02.1] Perceptrons (cont'd) | Lecture Slides Submit Result | |
| 09-13 | [Session 03.0] Loss functions | Lecture Slides Submit Result | Exercises Solution |
| 09-18 | [Session 03.1] Loss functions (cont'd) | Lecture Slides Submit Result | |
| 09-20 | [Session 04.0] Backpropagation | Lecture Slides Submit Result | Exercises Solution |
| 09-25 | [Session 04.1] Backpropagation (cont'd) | Lecture Slides Submit Result | |
| 09-27 | No Lecture (National Holiday) | ||
| 10-02 | No Lecture (National Holiday) | ||
| 10-04 | [Session 04.2] Backpropagation (cont'd) | Lecture Slides Submit Result | Exercises Solution |
| 10-09 | No Lecture (National Holiday) | ||
| 10-11 | [Session 05.0] Optimization | Lecture Slides Submit Result | Exercises Solution |
| 10-16 | [Session 05.1] Optimization (cont'd) | Lecture Slides Submit Result | |
| 10-18 | [Session 99.0] Midterm review (Q&A) | Exercises Solution | |
| 10-23 | [Session 99.1] Midterm | Solution Scores Claim Result | |
| 10-25 | No Lecture (Midterm Period) | ||
| 10-30 | [Session 06.0] CNNs | Lecture Slides Submit Result | |
| 11-01 | [Session 00.1] AI Days | Lecture Slides Submit Result | |
| 11-06 | [Session 06.1] CNNs (cont'd) | Lecture Slides Submit Result | |
| 11-08 | [Session 07.0] Word vectors | Lecture Slides Submit Result | Exercises Solution |
| 11-13 | [Session 07.1] Word vectors (cont'd) | Lecture Slides Submit Result | |
| 11-15 | [Session 08.0] RNNs | Lecture Slides Submit Result | Exercises Solution |
| 11-20 | [Session 08.1] RNNs (cont'd) | Lecture Slides Submit Result | |
| 11-22 | [Session 09.0] Seq2Seq | Lecture Slides Submit Result | Exercises Solution |
| 11-27 | [Session 09.1] Seq2Seq (cont'd) | Lecture Slides Submit Result | |
| 11-29 | [Session 10.0] Transformers | Lecture Slides Submit Result | Exercises Solution |
| 12-04 | [Session 10.1] Transformers (cont'd) | Lecture Slides Submit Result | |
| 12-06 | [Session 99.2] Final exam review (Q&A) | Exercises Solution | |
| 12-11 | [Session 99.3] Final exam | Solution Scores Claim Result | |
| 12-13 | No Lecture (Final Exam Period) | ||