Deep Learning with PyTorch

PyTorch

PyTorch, and most of the other deep learning frameworks, can be used for two different things:

• Replacing NumPy-like operations with GPU-accelerated operations
• Building deep neural networks

What makes PyTorch increasingly popular is its ease of use and simplicity. Unlike most other popular deep learning frameworks, which use static computation graphs, PyTorch uses dynamic computation, which allows greater flexibility in building complex architectures.

PyTorch extensively uses Python concepts, such as classes, structures, and conditional loops, allowing us to build DL algorithms in a pure object-oriented fashion. Most of the other popular frameworks bring their own programming style, sometimes making it complex to write new algorithms ...