pytorch-tutorial

Examples of deep learning basics
Dependencies
- Python 3.6+
- PyTorch==1.1
- Codes are heavily inspired by https://nextjournal.com/gkoehler

Name		Name	Last commit message	Last commit date
Latest commit History 14 Commits
00. LinearRegression.ipynb		00. LinearRegression.ipynb
01. DataLoader.ipynb		01. DataLoader.ipynb
02. LogisticRegression.ipynb		02. LogisticRegression.ipynb
03. Softmax Classification.ipynb		03. Softmax Classification.ipynb
04. MLP and XOR.ipynb		04. MLP and XOR.ipynb
05. f-MNIST with xavier.ipynb		05. f-MNIST with xavier.ipynb
06. f-MNIST with dropout and batch norm.ipynb		06. f-MNIST with dropout and batch norm.ipynb
07. RNN basic - character level language modeling.ipynb		07. RNN basic - character level language modeling.ipynb
08. RNN - stock market.ipynb		08. RNN - stock market.ipynb
09. seq2seq en-ko translation .ipynb		09. seq2seq en-ko translation .ipynb
10. PaddedSequence, PackedSequence.ipynb		10. PaddedSequence, PackedSequence.ipynb
11. CNN basic - CIFAR10.ipynb		11. CNN basic - CIFAR10.ipynb
12. VGGNet.ipynb		12. VGGNet.ipynb
13. ResNet.ipynb		13. ResNet.ipynb
14. ImageFolder.ipynb		14. ImageFolder.ipynb
15. Transfer Learning.ipynb		15. Transfer Learning.ipynb
16. Style Transfer (Gatys et al.).ipynb		16. Style Transfer (Gatys et al.).ipynb
README.md		README.md
dancing.jpg		dancing.jpg
data-02-stock_daily.csv		data-02-stock_daily.csv
picasso.jpg		picasso.jpg

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