Showing 4 open source projects for "model-builder"

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    Ship Agents Faster

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    Metarank

    Metarank

    A low code Machine Learning service that personalizes articles

    Metarank is a service that can personalize any type of content: product listings, articles, recommendations and search results in 3 easy steps with a few lines of code. It’s often considered "too risky" to spend 6+ months on an in-house moonshot project to reinvent the wheel without an experienced team and no existing open-source tools. Metarank makes it easy not only for Amazon to do personalization but for everyone else. Ingest historical item listings, clicks and item metadata so Metarank...
    Downloads: 2 This Week
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  • 2
    Aerosolve

    Aerosolve

    A machine learning package built for humans

    ...Built around sparse, human-intuitive features (like geography, pricing), it supports feature quantization, interaction specification, and rule-based priors—enabling domain experts to contribute directly to model behavior.
    Downloads: 0 This Week
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  • 3
    Synapse Machine Learning

    Synapse Machine Learning

    Simple and distributed Machine Learning

    SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit, and OpenCV. These tools enable powerful and highly-scalable predictive and analytical models for a variety of data sources. ...
    Downloads: 1 This Week
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  • 4
    PredictionIO

    PredictionIO

    Machine learning server for building predictive applications

    Apache PredictionIO is an open-source machine learning server designed to simplify the process of building and deploying predictive engines. It offers a scalable infrastructure with support for multiple ML algorithms, event data collection, and deployment workflows. Developers can use templates or build custom engines, making it a flexible solution for integrating machine learning into applications.
    Downloads: 0 This Week
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    MongoDB Atlas runs apps anywhere

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