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  2. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    In September 2022, Meta announced that PyTorch would be governed by the independent PyTorch Foundation, a newly created subsidiary of the Linux Foundation. [ 24 ] PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo , a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and ...

  3. PyTorch Lightning - Wikipedia

    en.wikipedia.org/wiki/PyTorch_Lightning

    PyTorch Lightning is an open-source Python library that provides a high-level interface for PyTorch, a popular deep learning framework. [1] It is a lightweight and high-performance framework that organizes PyTorch code to decouple research from engineering, thus making deep learning experiments easier to read and reproduce.

  4. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    It is designed to follow the structure and workflow of NumPy as closely as possible and works with TensorFlow as well as other frameworks such as PyTorch. The primary functions of JAX are: [71] grad: automatic differentiation; jit: compilation; vmap: auto-vectorization; pmap: SPMD programming

  5. User guide - Wikipedia

    en.wikipedia.org/wiki/User_guide

    Some usages are Installation Guide, Getting Started Guide, and various How to guides. An example is the Picasa Getting Started Guide. [5] In some business software applications, where groups of users have access to only a sub-set of the application's full functionality, a user guide may be prepared for each group.

  6. AOL Mail Help - AOL Help

    help.aol.com/products/new-aol-mail

    That's why AOL Mail Help is here with articles, FAQs, tutorials, our AOL virtual chat assistant and live agent support options to get your questions answered. You've Got Mail!® Millions of people around the world use AOL Mail, and there are times you'll have questions about using it or want to learn more about its features.

  7. Physics-informed neural networks - Wikipedia

    en.wikipedia.org/wiki/Physics-informed_neural...

    Physics-informed neural networks for solving Navier–Stokes equations. Physics-informed neural networks (PINNs), [1] also referred to as Theory-Trained Neural Networks (TTNs), [2] are a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process, and can be described by partial differential equations (PDEs).

  8. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python is a multi-paradigm programming language. Object-oriented programming and structured programming are fully supported, and many of their features support functional programming and aspect-oriented programming (including metaprogramming [71] and metaobjects). [72]

  9. Racket (programming language) - Wikipedia

    en.wikipedia.org/wiki/Racket_(programming_language)

    Racket is a general-purpose, multi-paradigm programming language.The Racket language is a modern dialect of Lisp and a descendant of Scheme.It is designed as a platform for programming language design and implementation. [9]