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  2. Google JAX - Wikipedia

    en.wikipedia.org/wiki/Google_JAX

    JAX is a machine learning framework for transforming numerical functions. [2] [3] [4] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and OpenXLA's XLA (Accelerated Linear Algebra).

  3. Google Brain - Wikipedia

    en.wikipedia.org/wiki/Google_Brain

    TensorFlow is an open source software library powered by Google Brain that allows anyone to utilize machine learning by providing the tools to train one's own neural network. [2] The tool has been used to develop software using deep learning models that farmers use to reduce the amount of manual labor required to sort their yield, by training ...

  4. Flux (machine-learning framework) - Wikipedia

    en.wikipedia.org/wiki/Flux_(machine-learning...

    Flux is an open-source machine-learning software library and ecosystem written in Julia. [1] [6] Its current stable release is v0.15.0 [4] .It has a layer-stacking-based interface for simpler models, and has a strong support on interoperability with other Julia packages instead of a monolithic design. [7]

  5. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    For example, TensorFlow Recommenders and TensorFlow Graphics are libraries for their respective functionalities in recommendation systems and graphics, TensorFlow Federated provides a framework for decentralized data, and TensorFlow Cloud allows users to directly interact with Google Cloud to integrate their local code to Google Cloud. [68]

  6. Keras - Wikipedia

    en.wikipedia.org/wiki/Keras

    Designed to enable fast experimentation with deep neural networks, Keras focuses on being user-friendly, modular, and extensible. It was developed as part of the research effort of project ONEIROS (Open-ended Neuro-Electronic Intelligent Robot Operating System), [5] and its primary author and maintainer is François Chollet, a Google engineer

  7. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]

  8. Andrew Ng - Wikipedia

    en.wikipedia.org/wiki/Andrew_Ng

    From 2011 to 2012, he worked at Google, where he founded and directed the Google Brain Deep Learning Project with Jeff Dean, Greg Corrado, and Rajat Monga. In 2014, he joined Baidu as chief scientist, and carried out research related to big data and AI. [ 27 ]

  9. Graph neural network - Wikipedia

    en.wikipedia.org/wiki/Graph_neural_network

    Modifying the final layer to be a fully-adjacent layer, i.e., by considering the graph as a complete graph, can mitigate oversquashing in problems where long-range dependencies are required. [ 37 ] Other "flavours" of MPNN have been developed in the literature, [ 12 ] such as graph convolutional networks [ 9 ] and graph attention networks, [ 11 ...

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