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PyTorch-Notes
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23 Commits
23 Commits
00.Tensors.ipynb
00.Tensors.ipynb
01.Gradients.ipynb
01.Gradients.ipynb
02.Backpropagation.ipynb
02.Backpropagation.ipynb
03.Gradient Descent and Backpropagation.ipynb
03.Gradient Descent and Backpropagation.ipynb
04.Gradient Descent and Backpropagation2.ipynb
04.Gradient Descent and Backpropagation2.ipynb
05.Gradient Descent and Backpropagation3.ipynb
05.Gradient Descent and Backpropagation3.ipynb
06.Gradient Descent and Backpropagation4.ipynb
06.Gradient Descent and Backpropagation4.ipynb
07.Linear Regression.ipynb
07.Linear Regression.ipynb
08.Logistic Regression.ipynb
08.Logistic Regression.ipynb
09.Dataset and Dataloader (Batch Training).ipynb
09.Dataset and Dataloader (Batch Training).ipynb
10.Dataset Transforms.ipynb
10.Dataset Transforms.ipynb
11.Softmax and Cross Entropy.ipynb
11.Softmax and Cross Entropy.ipynb
12.Activation Functions.ipynb
12.Activation Functions.ipynb
13.Feed Forward Neural Networks.ipynb
13.Feed Forward Neural Networks.ipynb
14.Conv Nets Helper.ipynb
14.Conv Nets Helper.ipynb
14.Convolutional Neural Networks.ipynb
14.Convolutional Neural Networks.ipynb
15. Helpful Torch Functions.ipynb
15. Helpful Torch Functions.ipynb
16. Transfer Learning.ipynb
16. Transfer Learning.ipynb
17.Tensor Board.ipynb
17.Tensor Board.ipynb
18. Saving and Loading Models.ipynb
18. Saving and Loading Models.ipynb
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PyTorch-Notes
Notes & implementation of useful PyTorch functions for future reference
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Notes & implementation of useful PyTorch functions for future reference
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