Learning PyTorch Core Concepts

PyTorch overview and purpose

PyTorch is an open-source deep learning library originally developed by Meta and now supported through the Linux Foundation. It provides a high-level API for building and training deep neural networks while relying on optimized low-level implementations for core operations and architectures (e.g., Transformers and SGD). This design helps simplify model training and inference to relatively few lines of code. Its purpose is to make deep learning development efficient and flexible by using tensors as the fundamental data type, supporting GPU acceleration via CUDA (and other backends such as ROCm and Metal), and enabling automatic differentiation through Autograd. During the forward pass, Autograd records operations to build a computation graph, and then backpropagation computes gradients needed for learning. PyTorch also includes tools for defining neural networks (via the nn module) and saving/loading models using its own serialized file format.

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PyTorch programming language and platforms

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