PyTorch is an open-source machine learning framework based on the Torch library, that allows you to build and deploy neural network models easily. It is used for applications such as computer vision and natural language processing, primarily developed by Facebook's AI Research (FAIR) lab. It is well-supported on major cloud platforms, providing frictionless development and easy scaling. Its Pythonic nature and the latest mobile model support have propelled PyTorch to such popularity, with its usage extending from research to industry. Today, leading companies like Tesla, Lyft, Disney, Microsoft, Airbnb, Toyota, Facebook (of course), etc. are using PyTorch frequently to help scale their deep learning models from research to deployment.
This is a repository of all notebooks and presentations used in PyTorch-101 workshop.
- Kindly open the notebooks in Colab using the "Open in Colab" button on top of each notebook.
- Try out the code by implementing the various PyTorch methods and functions. Use the Pytorch documentation to explore more.
- If you face any abnormal outputs, feel free to ping us.
Any doubts, feel free to ask your queries, especially those who couldn't attend at [email protected].
- Official Website
- PyTorch Intro Tutorial
- Fast-PyTorch
- Official Documentation
- Introduction to PyTorch by Analytics Vidhya
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