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    $300 Free Credits to Build on Google Cloud

    New to Google Cloud? Get $300 in credits to explore Compute Engine, BigQuery, Cloud Run, Gemini Enterprise Agent Platform, and more.

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  • 1
    Hivemind

    Hivemind

    Decentralized deep learning in PyTorch. Built to train models

    Hivemind is a PyTorch library for decentralized deep learning across the Internet. Its intended usage is training one large model on hundreds of computers from different universities, companies, and volunteers. Distributed training without a master node: Distributed Hash Table allows connecting computers in a decentralized network. Fault-tolerant backpropagation: forward and backward passes succeed even if some nodes are unresponsive or take too long to respond. Decentralized parameter averaging: iteratively aggregate updates from multiple workers without the need to synchronize across the entire network. ...
    Downloads: 0 This Week
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  • 2
    OpenCV

    OpenCV

    Open Source Computer Vision Library

    ...Languages: C++, Python, Julia, Javascript Homepage: https://opencv.org Q&A forum: https://forum.opencv.org/ Documentation: https://docs.opencv.org Source code: https://github.com/opencv Please pay special attention to our tutorials! https://docs.opencv.org/master Books about the OpenCV are described here: https://opencv.org/books.html
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    Downloads: 33,790 This Week
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  • 3
    Elephas

    Elephas

    Distributed Deep learning with Keras & Spark

    ...Keras Models are initialized on the driver, then serialized and shipped to workers, alongside with data and broadcasted model parameters. Spark workers deserialize the model, train their chunk of data and send their gradients back to the driver. The "master" model on the driver is updated by an optimizer, which takes gradients either synchronously or asynchronously. Hyper-parameter optimization with elephas is based on hyperas, a convenience wrapper for hyperopt and keras.
    Downloads: 0 This Week
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