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Deep Learning Practices Using Pytorch - Hands on Practice along with Theoretical Information

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.gitignore
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1.5.tensors.ipynb
1.5.tensors.ipynb
 
 
1.5.variables.ipynb
1.5.variables.ipynb
 
 
1.6.tensors.and.numpy.ipynb
1.6.tensors.and.numpy.ipynb
 
 
1.7.tensors.gpu.ipynb
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1.8.popular.datasets.ipynb
1.8.popular.datasets.ipynb
 
 
2.model.pth
2.model.pth
 
 
ANNs_2.png
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ANNs_3.png
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CPU_GPU_Pytorch.png
CPU_GPU_Pytorch.png
 
 
Concepts.png
Concepts.png
 
 
DL.png
DL.png
 
 
Deep Learning & PyTorch - Let the Game Begins!.ipynb
Deep Learning & PyTorch - Let the Game Begins!.ipynb
 
 
Dynamic_Static.png
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Handling Datasets in PyTorch.ipynb
Handling Datasets in PyTorch.ipynb
 
 
Installing CUDA.ipynb
Installing CUDA.ipynb
 
 
LICENSE
LICENSE
 
 
Loss Function and Optimizers in PyTorch.ipynb
Loss Function and Optimizers in PyTorch.ipynb
 
 
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Pytorch introduction and installation.ipynb
Pytorch introduction and installation.ipynb
 
 
Tensors and Variables - Intro.ipynb
Tensors and Variables - Intro.ipynb
 
 
Training a Neural Net.ipynb
Training a Neural Net.ipynb
 
 
activation_functions.png
activation_functions.png
 
 
cross_entropy_loss.png
cross_entropy_loss.png
 
 
example_1.png
example_1.png
 
 
example_2.png
example_2.png
 
 
loss_func.png
loss_func.png
 
 
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optimization.png
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optimization_pytorch.png
optimization_pytorch.png
 
 
optimizers_practice.png
optimizers_practice.png
 
 
pytorch_dl.png
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readme.md
readme.md
 
 
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Deep Learning Practices and Concepts Using Pytorch

Languages used:

  • Python 3.6

Libraries Used:

  • pandas
  • numpy
  • pytorch
  • seaborn

Make sure you have installed all the dependenicies and libraries compatible with python 3.6 to run the codes. A requirement.txt file will be added soon

About

Deep Learning Practices Using Pytorch - Hands on Practice along with Theoretical Information

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