AI Experience Laboratory

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:
Jae-Woo, Kim (kjw01124@gm.gist.ac.kr)
Won-Sic, Jang (wonsicjang@gm.gist.ac.kr)

Notice

• Review report format available here
• Recitations start from September 11 :)

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