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- 03 - Working with Classes and Tensors/01 - Classes.mp4 51.3 MB
- 04 - Working with Loss, Autograd, and Optimizers/01 - Loss.mp4 43.4 MB
- 02 - Fashion MNIST and Neural Networks/01 - Working with the Fashion MNIST dataset.mp4 34.8 MB
- 05 - Troubleshooting and CPUGPU Usage/02 - CPU to GPU.mp4 15.5 MB
- 06 - Conclusion/01 - Future project ideas.mp4 15.1 MB
- 05 - Troubleshooting and CPUGPU Usage/01 - Troubleshooting.mp4 12.0 MB
- 04 - Working with Loss, Autograd, and Optimizers/02 - Autograd.mp4 11.3 MB
- 02 - Fashion MNIST and Neural Networks/02 - Neural network intuition.mp4 11.1 MB
- 04 - Working with Loss, Autograd, and Optimizers/05 - Using optimizers.mp4 10.5 MB
- 01 - Introduction/01 - Welcome.mp4 9.9 MB
- 04 - Working with Loss, Autograd, and Optimizers/03 - Autograd with tensors.mp4 9.4 MB
- 05 - Troubleshooting and CPUGPU Usage/03 - Validation.mp4 8.1 MB
- 03 - Working with Classes and Tensors/02 - Tensors.mp4 7.6 MB
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- 01 - Introduction/02 - What you should know before watching this course.mp4 4.0 MB
- 04 - Working with Loss, Autograd, and Optimizers/04 - Optimizers.mp4 3.0 MB
- Exercise Files/Ex_Files_PyTorch_EssT_DL.zip 53.1 kB
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- 06 Logistic Regression with PyTorch/024 Logistic Regression with PyTorch.mp4 123.9 MB
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- 06 Logistic Regression with PyTorch/023 Logistic Regression In-depth.mp4 26.2 MB
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- 03 PyTorch Fundamentals_ Matrices/012 Basic Mathematical Tensor Operations.mp4 22.2 MB
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- 6.Movie Rating Using a Autoencoders/23.Making Autoencoders.mp4 23.8 MB
- 2.Convolutional Neural Network/06.Looking into Images from a Machine Perspective.mp4 23.4 MB
- 2.Convolutional Neural Network/09.Output Layer.mp4 21.5 MB
- 2.Convolutional Neural Network/08.Pooling Layers.mp4 19.5 MB
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- 5.Getting Some Culture - Becoming a Deep Neural Picasso with DNN/19.Building and Training Style Transfer Model.mp4 72.6 MB
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- 1.First Stop - A Quick Introduction to PyTorch/01.The Course Overview.mp4 12.2 MB
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- P35 Lesson21 MLP反向传播.mp4 86.0 MB
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