Simple PyTorch Tutorials Zero to ALL!
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hunkim Merge pull request #22 from jaejun-yoo/patch-1
Remove unnecessary parenthesis
Latest commit edd7ba1 Mar 28, 2018
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data Added name_classify Nov 3, 2017
slides Updated slides Nov 12, 2017
.gitignore Fixed bugs Nov 11, 2017
.travis.yml Added travis Nov 11, 2017
01_basics.py Updated PDFs Oct 11, 2017
02_manual_gradient.py fixed GPU Oct 22, 2017
03_auto_gradient.py Updated PDFs Oct 11, 2017
05_linear_regression.py Added slides and new videos Oct 28, 2017
06_logistic_regression.py Added slides and new videos Oct 28, 2017
07_diabets_logistic.py Added name_classify Nov 3, 2017
08_1_dataset_loader.py Added name_classify Nov 3, 2017
08_2_dataset_loade_logistic.py Updated slides Nov 12, 2017
09_01_softmax_loss.py Added more lectures Oct 29, 2017
09_2_softmax_mnist.py Fixed softmax mnist Nov 15, 2017
10_1_cnn_mnist.py Added inceptipn and basic RNNs Oct 8, 2017
11_1_toy_inception_mnist.py Added char rnn and seq2seq Oct 31, 2017
12_1_rnn_basics.py Remove unnecessary parenthesis Mar 27, 2018
12_2_hello_rnn.py Fixed rnn hidden shape bugs Mar 24, 2018
12_3_hello_rnn_seq.py Fixed rnn hidden shape bugs Mar 24, 2018
12_4_hello_rnn_emb.py Fixed rnn hidden shape bugs Mar 24, 2018
13_1_rnn_classification_basics.py Updated slides Nov 12, 2017
13_2_rnn_classification.py Updated slides Nov 12, 2017
13_3_char_rnn.py Updated slides Nov 12, 2017
13_4_pack_pad.py Updated slides Nov 12, 2017
14_1_seq2seq.py Fixed bugs Nov 11, 2017
14_2_seq2seq_att.py Updated slides Nov 12, 2017
README.md Merge branch 'master' of github.com:hunkim/PyTorchZeroToAll Nov 12, 2017
name_dataset.py Added fixed code Nov 3, 2017
requirements.txt Added name_classify Nov 3, 2017
seq2seq_models.py Simplified RNN/Att Nov 8, 2017
text_loader.py Added fixed code Nov 3, 2017

README.md

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PyTorchZeroToAll

Quick 3~4 day lecture materials for HKUST students.

Video Lectures: (RNN TBA)

Slides

If you cannot access the GoogleDoc for somehow, please check out pdf files in slides. However, slides in GoogleDrive are always latest. We really appreciate your comments.

Previous Lectures