Torch

PyTorch is an open-source machine learning library developed by Facebook's AI Research lab, used for applications such as computer vision and natural language processing. It provides dynamic computation graphs that enable users to build and execute complex neural networks with ease.

Here are some key features and capabilities of PyTorch:

1. Dynamic computation graphs: PyTorch allows you to define and modify computations on the fly, making it easy to debug and experiment with different architectures.
2. Rich ecosystem: PyTorch has a vast ecosystem of tools and libraries built around it, such as:
   • TorchScript: A tool for creating serializable and optimizable models from PyTorch.
   • PyTorch Lightning: A high-level research framework that provides tools for scalable deep learning.
   • Fast.ai: A library that focuses on making deep learning accessible and practical through fast, easy-to-use, and well-documented code.
3. Efficient memory management: PyTorch uses a custom CUDA memory allocator to reduce GPU memory fragmentation and improve performance.
4. Seamless integration with other libraries: PyTorch can be easily integrated with popular data science and machine learning libraries like NumPy, SciPy, and Matplotlib for better interoperability.
5. Extensive documentation and community support: PyTorch has extensive documentation, tutorials, and a large, active community that contributes to its development and provides help to users.

Installation⚑

Select your preferences in this web and run the install command

References⚑

• Source
• Homepage
• Docs
• Tutorials:
  • Official Tutorials
  • User guide (Tensor Tutorial): Tensor Basics