PyTorch is an open-source machine learning framework developed by Facebook's AI Research lab. It is widely used for applications such as computer vision, natural language processing, and generative modeling. Here's a quick guide to its key features:

🌟 Core Features

  • Dynamic Computation Graphs ⚙️
    PyTorch uses a dynamic computational graph (e.g., torch.nn.Module), allowing flexible model design and debugging.

    PyTorch Logo

  • Automatic Differentiation 📈
    Built-in support for automatic differentiation via torch.autograd, simplifying gradient computation.

    Automatic Differentiation

  • Rich Ecosystem 🌐
    Includes tools like torchvision for vision tasks, torchaudio for audio, and pytorch-lightning for scalable training.

    Ecosystem

📘 Why Choose PyTorch?

  • Ideal for research and prototyping due to its Pythonic design
  • Strong community support and active development
  • Seamless integration with other frameworks (e.g., TensorFlow via torch2tf)

For deeper exploration, check our PyTorch Quickstart Tutorial to get hands-on experience! 🚀
Want to dive into specific use cases? Explore /en/learn/tutorials/beginner for beginner-friendly examples.