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Announcements: All grades are posted in Canvas, we will post your final grade by March 20 mid-night.
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WeekDatesTopicsTextbook ReadingExtra Readings (T)Extra Readings (R)ProjectSlides (T)Slides (R)Lecture Video (T)Lecture Video (R)
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11.4 1.6-- Introduction
-- ML Basics		-- Chapter 2 (Optional)
-- Chapter 5		-- ML Basics-- Introduction-- ML BasicsIntroduction Part 1 - Part 6ML Basics Part 1 - Part 6
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21.11 1.13-- Project & Pytorch
-- Stochastic Optimization		-- Chapter 7
-- Chapter 8		-- Gradient DescentStage 1
(Team Formation & Environment Setup)
Due by 11:59pm, Friday		-- Project-- OptimizationNAOptimization Part 1 - Part 6
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31.18 1.20-- DL Basics
-- Auto-Encoder		-- Chapter 6
-- Chapter 14		-- Brain Tutorial 1 (Optional)-- Brain Tutorial 2 (Optional)-- DL Basics-- AutoencoderDL Basics Part 1 - Part 6Autoencoder Part 1 - Part 6
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41.25 1.27-- Auto-Encoder
-- CNN		-- Chapter 9
-- Chapter 12		VAE (Section 2, Optional)-- CNNStage 2
(MLP with Pytorch)
Due by 11:59pm, Friday		-- Autoencoder-- CNNAutoencoder Part 1 - Part 6CNN Part 1 - Part 6
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52.1 2.3-- Computer Vision
-- GAN		-- Chapter 20-- GAN-- Computer Vision-- GANCV Part 1 - Part 6GAN Part 1 - Part 6
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62.8 2.10-- Mid-Term Overview
-- Mid-Term Exam (no class)		Stage 3
(Image Recognition with CNN)
Due by 11:59pm, Sunday		-- Mid-termNAMid-term OverviewNA
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72.15 2.17-- RNN
-- LSTM		-- Chapter 10
-- LSTM-- RNN-- LSTMRNN Part 1 - Part 3RNN Part 4 - Part 6
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82.22 2.24-- Word Embedding
-- Transformer & BERT		-- Chapter 12-- Transformer-- BERTStage 4
(Text Classification and Generation with RNN)
Due by 11:59pm, Monday		-- NLP-- TransformerNLP Part 1 - Part 6Transformer Part 1 - Part 6
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93.1 (quiz) 3.3-- GNN
-- Network Embedding		-- GCN-- NE-- GNN-- Network EmbeddingGNN Part 1 - Part 6NE Part 1 - Part 6
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103.8 3.10-- Graph-Bert
--- Final Overview		-- Graph-Bert-- GResNetStage 5
(Graph Representation Learning with GCN)
Due by 11:59pm, Friday		-- Graph-Bert-- FinalGraph-Bert Part 1 - Part 6Final Overview
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11Final Exam Week-- Final Exam
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