PyTorch is a software-based open source deep learning framework used to build neural networks, combining the machine learning (ML) library of Torch with a Python-based high-level API. Its flexibility and ease of use, among other benefits, have made it the leading ML framework for academic and research communities.
PyTorch supports a wide variety of neural network architectures, from simple linear regression algorithms to complex convolutional neural networks and generative transformer models used for tasks like computer vision and natural language processing (NLP). Built on the widely understood Python programming language and offering extensive libraries of pre-configured (and even pre-trained) models, PyTorch allows data scientists to build and run sophisticated deep learning networks while minimizing the time and labor spent on code and mathematical structure.
PyTorch also allows data scientists to run and test portions of code in real time, rather than wait for the entire code to be implemented—which, for large deep learning models, can take a very long time. This makes PyTorch an excellent platform for rapid prototyping, and also greatly expedites the debugging process.
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