PyTorch - Deep Learning & Tensors

PyTorch is a Python-based scientific computing package that uses the power of Graphics Processing Units (GPUs) and provides maximum flexibility and speed through its dynamic computational graph system.

When to Use

• Building and training Deep Neural Networks (CNN, RNN, Transformers).
• Researching new AI architectures with dynamic graph needs.
• Accelerating tensor math on NVIDIA (CUDA) or Mac (MPS) hardware.
• Solving Physics-Informed Neural Networks (PINNs).
• Implementing Generative models (GANs, Diffusion).
• Large-scale optimization using Autograd (automatic differentiation).
• Production-grade AI deployment (via TorchScript/ONNX).

Reference Documentation

Official docs: https://pytorch.org/docs/
Tutorials: https://pytorch.org/tutorials/
Search patterns: torch.nn, torch.optim, torch.utils.data, Autograd, Tensor.to(device)