Showing 3 open source projects for "risk"

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  • 1
    InterpretML

    InterpretML

    Fit interpretable models. Explain blackbox machine learning

    In the beginning, machines learned in darkness, and data scientists struggled in the void to explain them. InterpretML is an open-source package that incorporates state-of-the-art machine-learning interpretability techniques under one roof. With this package, you can train interpretable glass box models and explain black box systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions.
    Downloads: 5 This Week
    Last Update:
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  • 2
    MNN

    MNN

    MNN is a blazing fast, lightweight deep learning framework

    ...At present, MNN has been integrated in more than 20 apps of Alibaba Inc, such as Taobao, Tmall, Youku, Dingtalk, Xianyu and etc., covering more than 70 usage scenarios such as live broadcast, short video capture, search recommendation, product searching by image, interactive marketing, equity distribution, security risk control. In addition, MNN is also used on embedded devices, such as IoT. MNN Workbench could be downloaded from MNN's homepage, which provides pretrained models, visualized training tools, and one-click deployment of models to devices. Android platform, core so size is about 400KB, OpenCL so is about 400KB, Vulkan so is about 400KB. ...
    Downloads: 71 This Week
    Last Update:
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  • 3
    OpenMLDB

    OpenMLDB

    OpenMLDB is an open-source machine learning database

    ...It prioritizes the capability of feature engineering using SQL for open-source, which offers a feature platform enabling consistent features for training and inference. Real-time features are essential for many machine learning applications, such as real-time personalized recommendations and risk analytics. However, a feature engineering script developed by data scientists (Python scripts in most cases) cannot be directly deployed into production for online inference because it usually cannot meet the engineering requirements, such as low latency, high throughput and high availability.
    Downloads: 0 This Week
    Last Update:
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