CSCI6379 Intro to Deep Learning

Jan. 22

Course intro, Research Guide, AI and ML intro

1a, 1b, 2, 3, 4, 5, 6, 7

0, 1, 2, 3

Lab 1, 3, 4, 5, 6

3

Jan. 29

Linear Regression, MSE, Gradient Descent Algorithm, Normazliation, Linear Classifier, Logistic Regression, Neural Network

8, 9, 10, 11, 12, 13, 14, 15

15

Lab 8~15

8~15, 16

Feb. 5

CNN

17, 18

17~18

Lab17

17~18

hw1-1

Feb. 12

CNN and Transfer Learning

19, 20, 25

19, 21, 22, 23, 24, 25, dogs-vs-cats.zip, apple.zip

Project Proposal

Feb. 19

HW1-2, Proposal Review, GPU Cluster, GAN

31, 32, 33, 34, 35, 36

Lab 34, 35

HW1-2 Reference Code

HW1-2

Feb. 26

GAN Review and RL Part1

RL1

March 4

Literature Review and RL Part2

RL2

1, 2, 3, 4, 5

March 11

Spring Break

March 18

Literature Reviews

5, 12, 13, 3, 2, 7, 4

March 25

Literature Reviews

9, 8, 11, 1, 6, 14, 10

April 1

HW2-GAN, RL Part3, AE

RL3, AE

dqn, reinforcement, actor_critic, autoencoder

HW2, HW2-Ref

April 8

HW3, RNN, LSTM, Embedding

HW3, HW3-ref

April 15

KL Divergence, VAE, RNN Review, Embedding, GNN, GCN

41, 42, 43, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 70, 71, 72, 73, 74