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layout page
title Schedule
permalink /schedule/
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Lecture Feb. 6 overview and simple perceptron  
Lecture Feb. 8 delta rule  
Pset 1 due Feb. 13 simple perceptrons  
Lecture Feb. 13 multilayer perceptrons  
Lecture Feb. 15 backpropagation  
Pset 2 due Feb. 20 multilayer perceptrons  
Lecture Feb. 20 stochastic gradient descent  
Lecture Feb. 22 generalization and regularization  
Pset 3 due Feb. 27 black art of backprop  
Lecture Feb. 27 convolution and pooling  
Lecture Mar. 1 ConvNet backprop  
Pset 4 due Mar. 6 LeNet  
Lecture Mar. 6 contemporary ConvNets  
Lecture Mar. 8 midterm review  
Lecture Mar. 13 biological vision  
Midterm Mar. 15 in-class exam  
Spring break      
Lecture Mar. 27 deep learning frameworks  
Lecture Mar. 29 parallel and distributed algorithms  
Pset 5 due Apr. 3 ConvNets at scale  
Lecture Apr. 3 competitive learning and clustering  
Lecture Apr. 5 principal component analysis  
Pset 6 due Apr. 10 unsupervised learning  
Lecture Apr. 10 autoencoders  
Lecture Apr. 12 n-grams and word embeddings  
Pset 7 due Apr. 17 word embeddings  
Lecture Apr. 17 backprop through time  
Lecture Apr. 19 class cancelled  
Lecture Apr. 24 RNNs for language  
Lecture Apr. 26 policy gradient  
Lecture May 1 AlphaGo case study  
Lecture May 3 final review  
Pset 8 due May 10 recurrent nets  
Final May 22 final exam