Code CSED538 or AIGS538
Term Spring 2023
Audience PG and UG students at POSTECH
Lectures Tuesdays and Thursdays 9:30am-10:45am (Room 506 in Library bldg)
Office hours Wednesdays 5-6pm (by appointment)
Online PLMS
Instructor Namhoon Lee
TA
Jinho Ko, JaeHyeok An, Donghyun Oh, Kwonyoung Ryu
Feb 21 (Tue)
Course logistics
Feb 23 (Thr)
Introduction
Feb 28 (Tue)
Linear Algebra
Mar 2 (Thr)
Probability
Mar 7 (Tue)
Numerical computation
Mar 9 (Thr)
ML basics 1
Mar 14 (Tue)
ML basics 2
Mar 16 (Thr)
Feedforward neural networks 1
Mar 21 (Tue)
Feedforward neural networks 2
Mar 23 (Thr)
Regularization 1
Mar 28 (Tue)
Regularization 2
Mar 30 (Thr)
Optimization 1
Apr 4 (Tue)
Optimization 2
Apr 6 (Thr)
Convolutional neural networks
Apr 11 (Feb) Midterm exam
Apr 18 (Tue)
Recurrent neural networks 1
Apr 20 (Thr)
Recurrent neural networks 2
Apr 25 (Tue)
TBA
Apr 27 (Thr)
TBA
May 2 (Tue)
Graph neural networks 1
May 4 (Thr)
Graph neural networks 2
May 9 (Tue)
Attention
May 11 (Thr)
Autoencoders
May 16 (Tue)
Generative models
May 18 (Thr)
Advanced topics 1
May 23 (Tue)
Advanced topics 2
May 25 (Thr)
Summary
May 30 (Tue)
Term project 1
Jun 1 (Thr)
Term project 2
Jun 8 (Thr)
Term project 3
The schedule is subject to change, and the slides will be made available on PLMS.
TBA
Assignments 20%
Midterm exam 20%
Quizzes 15%
Term project 45%
This course is based on Deep Learning book and will follow the previous deep learning courses at POSTECH.