CSE 4095/5095
 Deep Learning


Course Schedule

(Tentative schedule for the course and deviations may be necessary as the course progresses.)

Date Topic Notes Reading (Textbook or Other Materials)
Aug. 25 Introduction Chapter 1, 2, 3, Nature review on DL, Basic calculus refresher
Aug. 27, 29 Machine Learning Basics Chapter 4, 5, Machine learning math essentials
Sept. 3 Shallow Classifiers
Project Details
Chapter 4, 5
Sept. 5 Loss Functions
Chapter 4, 5
Sept. 8, 12
Optimization, SGD
Chapter 4, 5
Sept. 15 Backpropagation Chapter 4, 5
Sept. 17, 19 Intro to Neural Networks
Sept. 22 Intro to Convolutional Neural Networks, Convolution AlexNet
Sept. 24, 26 Pooling, Demo, BP example All Convolutional Net
Sept. 29 Training Neural Networks
Oct. 1 Training Neural Networks II, Batch Normalization Batch Normalization
Oct. 6 Second-order Optimization Chapter 8
Oct. 8 Regularization, Transfer Learning Dropout, Blackout, DeCAF
Oct. 13 ImageNet, CNN Architectures AlexNet, VGGNet, GoogleNet, ResNet
Oct. 15 Visualization Yosinski et al.
Oct. 20 Word2Vec
word2vec, glove, wordrank
Oct. 22 RNN rnnlm
Oct. 27 LSTM, GRU LSTM, GRU
Oct. 29 Image Caption, Machine Translation Show, Attend and Tell, NMT with Attention
Nov. 3 Transformer Attention is All You Need, The Illustrated Transformer
Nov. 5 AutoEncoder, VAE VAE
Nov. 10 Generative Adversial Networks GAN, DCGAN
Nov. 12 Diffusion Models DDPM, Stable Diffusion
Nov. 17 Review
Nov. 19 Presentation
Nov. 24 - 28 No classes Thanksgiving Recess
Dec. 1 Presentation
Dec. 3 Review
Dec. 9 Final Exam
Dec. 12 Project Report Due (by 11:59 pm)

 

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