Showing 4 open source projects for "commercial"

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  • 1
    Python Outlier Detection

    Python Outlier Detection

    A Python toolbox for scalable outlier detection

    ...PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural network-based models, e.g., AutoEncoders, which are implemented in both PyTorch and Tensorflow. PyOD contains multiple models that also exist in scikit-learn. It is possible to train and predict with a large number of detection models in PyOD by leveraging SUOD framework. A benchmark is supplied for select algorithms to provide an overview of the implemented models. ...
    Downloads: 0 This Week
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  • 2
    SOD

    SOD

    An Embedded Computer Vision & Machine Learning Library

    SOD is an embedded, modern cross-platform computer vision and machine learning software library that expose a set of APIs for deep-learning, advanced media analysis & processing including real-time, multi-class object detection and model training on embedded systems with limited computational resource and IoT devices. SOD was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in open source as well as commercial products. SOD implements state-of-the-art computer vision algorithms found to be mandatory in real-world application areas. Sobel operator, Otsu's binarization and over 100 image/frame processing & analysis interfaces. Designed for computational efficiency and with a strong focus on real-time applications. SOD includes a comprehensive set of both classic and state-of-the-art deep-neural networks with their pre-trained models.
    Downloads: 0 This Week
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  • 3
    The fastai book

    The fastai book

    The fastai book, published as Jupyter Notebooks

    ...The remainder (including all markdown cells in the notebooks and other prose) is not licensed for any redistribution or change of format or medium, other than making copies of the notebooks or forking this repo for your own private use. No commercial or broadcast use is allowed. We are making these materials freely available to help you learn deep learning, so please respect our copyright and these restrictions.
    Downloads: 0 This Week
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  • 4
    Microsoft Cognitive Toolkit (CNTK)

    Microsoft Cognitive Toolkit (CNTK)

    Open-source toolkit for commercial-grade distributed deep learning

    CNTK describes neural networks as a series of computational steps via a digraph which are a set of nodes or vertices that are connected with the edges directed between different vertexes. Create and combine models such as: -Feed-Forward DNNs -Convolutional neural networks -Recurrent neural networks
    Downloads: 1 This Week
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