Browse free open source Neural Network Libraries and projects for Linux below. Use the toggles on the left to filter open source Neural Network Libraries by OS, license, language, programming language, and project status.

  • Train ML Models With SQL You Already Know Icon
    Train ML Models With SQL You Already Know

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    Paessler: Easy to Use With Enterprise Power. Free Trial

    A low-code dashboard makes monitoring intuitive for any admin, while scripting and custom sensors give experts full control.

    You shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
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  • 1
    Frevo

    Frevo

    Frevo is probably the simplest tool for evolutionary design

    FREVO is an open-source framework developed in Java to help engineers and scientists in evolutionary design or optimization tasks. The major feature of FREVO is the componentwise decomposition and separation of the key building blocks for each optimization tasks. We identify these as the problem definition, solution representation and the optimization method. This structure enables the components to be designed separately allowing the user to easily swap and evaluate different configurations and methods or to connect an external simulation tool. The latest version in development is hosted at https://github.com/smartgrids-aau/Frevo
    Downloads: 10 This Week
    Last Update:
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  • 2
    DaNNet

    DaNNet

    Deep Artificial Neural Network framework using Armadillo

    DaNNet is a C++ deep neural network library using the Armadillo library as a base. It is intended to be a small and easy to use framework with no other dependencies than Armadillo. It uses independent layer-wise optimization giving you full flexibility to train your network.
    Downloads: 0 This Week
    Last Update:
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  • 3
    Lucid

    Lucid

    A collection of infrastructure and tools for research

    Lucid is a collection of infrastructure and tools for research in neural network interpretability. Lucid is research code, not production code. We provide no guarantee it will work for your use case. Lucid is maintained by volunteers who are unable to provide significant technical support. Start visualizing neural networks with no setup. The following notebooks run right from your browser, thanks to Collaboratory. It's a Jupyter notebook environment that requires no setup to use and runs entirely in the cloud. You can run the notebooks on your local machine, too. Clone the repository and find them in the notebooks subfolder. You will need to run a local instance of the Jupyter notebook environment to execute them. Feature visualization answers questions about what a network, or parts of a network, are looking for by generating examples.
    Downloads: 0 This Week
    Last Update:
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