Link: https://pytorch.org/
Description: WEBLearn how our community solves real, everyday machine learning problems with PyTorch. Developer Resources. Find resources and get questions answered. Events. Find events, webinars, and podcasts. Forums. A place to discuss PyTorch code, issues, install, research. Models (Beta) Discover, publish, and reuse pre-trained models
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Link: https://pytorch.org/get-started/locally/
Description: WEBCurrently, PyTorch on Windows only supports Python 3.8-3.11; Python 2.x is not supported. As it is not installed by default on Windows, there are multiple ways to install Python: Chocolatey; Python website; Anaconda; If you use Anaconda to install PyTorch, it will install a sandboxed version of Python that will be used for running PyTorch ...
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Link: https://en.wikipedia.org/wiki/PyTorch
Description: WEBPyTorch is a machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, originally developed by Meta AI and now part of the Linux Foundation umbrella.
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Link: https://pytorch.org/docs/stable/index.html
Description: WEBPyTorch is an optimized tensor library for deep learning using GPUs and CPUs. Features described in this documentation are classified by release status: Stable: These features will be maintained long-term and there should generally be no major performance limitations or gaps in documentation.
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Link: https://pytorch.org/get-started/pytorch-2.0/
Description: WEBIntroducing PyTorch 2.0, our first steps toward the next generation 2-series release of PyTorch. Over the last few years we have innovated and iterated from PyTorch 1.0 to the most recent 1.13 and moved to the newly formed …
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Link: https://pytorch.org/tutorials/
Description: WEBLearn the Basics. Familiarize yourself with PyTorch concepts and modules. Learn how to load data, build deep neural networks, train and save your models in this quickstart guide. Get started with PyTorch.
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Link: https://github.com/pytorch/pytorch
Description: WEBPyTorch is a Python package that provides two high-level features: Tensor computation (like NumPy) with strong GPU acceleration. Deep neural networks built on a tape-based autograd system. You can reuse your favorite Python packages such as NumPy, SciPy, and Cython to extend PyTorch when needed.
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Link: https://pytorch.org/tutorials/beginner/basics/intro.html
Description: WEBLearn the Basics. Authors: Suraj Subramanian , Seth Juarez , Cassie Breviu , Dmitry Soshnikov , Ari Bornstein. Most machine learning workflows involve working with data, creating models, optimizing model parameters, and saving the trained models. This tutorial introduces you to a complete ML workflow implemented in PyTorch, with links to learn ...
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Link: https://pytorch.org/features/
Description: WEBPyTorch enables fast, flexible experimentation and efficient production through a user-friendly front-end, distributed training, and ecosystem of tools and libraries. Get Started.
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Link: https://pytorch.org/tutorials/beginner/pytorch_with_examples.html
Description: WEBThis is one of our older PyTorch tutorials. You can view our latest beginner content in Learn the Basics. This tutorial introduces the fundamental concepts of PyTorch through self-contained examples. At its core, PyTorch provides two main features: An n-dimensional Tensor, similar to numpy but can run on GPUs.
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