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    Deep Java Library (DJL)

    Deep Java Library (DJL)

    An engine-agnostic deep learning framework in Java

    Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. DJL is designed to be easy to get started with and simple to use for Java developers. DJL provides native Java development experience and functions like any other regular Java library. You don't have to be a machine learning/deep learning expert to get started.
    Downloads: 1 This Week
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    GROBID

    GROBID

    A machine learning software for extracting information

    GROBID is a machine learning library for extracting, parsing, and re-structuring raw documents such as PDF into structured XML/TEI encoded documents with a particular focus on technical and scientific publications. First developments started in 2008 as a hobby. In 2011 the tool has been made available in open source. Work on GROBID has been steady as a side project since the beginning and is expected to continue as such. Header extraction and parsing from article in PDF format. The...
    Downloads: 7 This Week
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  • 3
    The Julia Programming Language

    The Julia Programming Language

    High-level, high-performance dynamic language for technical computing

    ...Julia has more than 2,800 community-registered packages including various mathematical libraries, data manipulation tools, and packages for general purpose computing. Libraries from Python, R, C/Fortran, C++, and Java can also be used.
    Downloads: 18 This Week
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    tvm

    tvm

    Open deep learning compiler stack for cpu, gpu, etc.

    ...Compilation of deep learning models in Keras, MXNet, PyTorch, Tensorflow, CoreML, DarkNet and more. Start using TVM with Python today, build out production stacks using C++, Rust, or Java the next day.
    Downloads: 0 This Week
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    OpenCV

    OpenCV

    Open Source Computer Vision Library

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    Downloads: 3,009 This Week
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    Apache MXNet (incubating)

    Apache MXNet (incubating)

    A flexible and efficient library for deep learning

    Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable.
    Downloads: 1 This Week
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  • 7
    MXNet

    MXNet

    Lightweight, Portable, Flexible Distributed/Mobile Deep Learning

    Apache MXNet is a scalable, efficient open-source deep learning framework—offering a flexible hybrid programming model (symbolic + imperative) and supporting a wide array of languages—designed for training and deploying neural networks across heterogeneous systems. Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic...
    Downloads: 0 This Week
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  • 8
    MIT Deep Learning Book

    MIT Deep Learning Book

    MIT Deep Learning Book in PDF format by Ian Goodfellow

    The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free. MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville. An MIT Press book Ian Goodfellow and Yoshua Bengio and Aaron Courville. Written by three experts in the field, Deep Learning is...
    Downloads: 6 This Week
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  • 9
    Seldon Server

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    Machine learning platform and recommendation engine on Kubernetes

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    Downloads: 0 This Week
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    Track calls, leads, and clicks without the manual work

    Automatically tie revenue back to campaigns, channels, publishers, and networks through marketing attribution. Spend less time juggling reports, and more time optimizing for growth by using a single operating solution for partner and performance marketing.
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  • 10
    NNVM

    NNVM

    Open deep learning compiler stack for cpu, gpu

    The vision of the Apache NNVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging machine learning models for any hardware platform. Compilation of deep learning models into minimum deployable modules. Infrastructure to automatically generates and optimize models on more backend with better performance....
    Downloads: 0 This Week
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