Showing 3 open source projects for "kde based distros"

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    Atera all-in-one platform IT management software with AI agents

    Ideal for internal IT departments or managed service providers (MSPs)

    Atera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
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  • Total Network Visibility for Network Engineers and IT Managers Icon
    Total Network Visibility for Network Engineers and IT Managers

    Network monitoring and troubleshooting is hard. TotalView makes it easy.

    This means every device on your network, and every interface on every device is automatically analyzed for performance, errors, QoS, and configuration.
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  • 1
    Spektral

    Spektral

    Graph Neural Networks with Keras and Tensorflow 2

    Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to provide a simple but flexible framework for creating graph neural networks (GNNs). You can use Spektral for classifying the users of a social network, predicting molecular properties, generating new graphs with GANs, clustering nodes, predicting links, and any other task where data is described by graphs.
    Downloads: 0 This Week
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  • 2

    Arabic Corpus

    Text categorization, arabic language processing, language modeling

    The Arabic Corpus {compiled by Dr. Mourad Abbas ( http://sites.google.com/site/mouradabbas9/corpora ) The corpus Khaleej-2004 contains 5690 documents. It is divided to 4 topics (categories). The corpus Watan-2004 contains 20291 documents organized in 6 topics (categories). Researchers who use these two corpora would mention the two main references: (1) For Watan-2004 corpus ---------------------- M. Abbas, K. Smaili, D. Berkani, (2011) Evaluation of Topic Identification Methods on...
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    Downloads: 1 This Week
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  • 3
    TexLexAn is an open source text analyser for Linux, able to estimate the readability and reading time, to classify and summarize texts. It has some learning abilities and accepts html, doc, pdf, ppt, odt and txt documents. Written in C and Python.
    Downloads: 0 This Week
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