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Code snippets and applications explained in the book - HandsOnDeepLearningWithPytorch
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1.Introduction
2.ASimpleNeuralNetwork
3.DLWorkFlow
4.ComputerVision
5.SequentialDataProcessing
6.GenerativeNetworks
7.ReinforcementLearning
8.PyTorchInProduction
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LICENSE
README.rst
environment.yml
utils.py

README.rst

HandsOnDeepLearningWithPytorch

Repository is arranged chapter wise and each folder includes the code used + the visualization of models use. Dataset used for the models are either available in the shared box folder or downloadable from the torch utility packages such as torchvision, torchtext or torchaudio

Chapters

  1. Introduction
  2. A Simple Neural Network
  3. Deep Learning work flow
  4. Computer Vision
  5. Sequential Data Processing
  6. Generative Networks
  7. Reinforcement Learning
  8. PyTorch In Production

Utilities

  • Visualization is handled by Netron -

    pip install netron
    
  • Environment is handled by Pipenv

Usage

  • Clone the repository

    git clone https://github.com/hhsecond/HandsOnDeepLearningWithPytorch.git && cd HandsOnDeepLearningWithPytorch
    
  • Install dependancies. HandsOnDeepLearningWithPytorch is using conda with python3.7

    conda env create -f environment.yml
    
  • CD to chapter directores and execute the models

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