Showing 5 open source projects for "data modeling"

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  • 1
    Meridian

    Meridian

    Meridian is an MMM framework

    ...The framework provides a robust foundation for constructing in-house MMM pipelines capable of handling both national and geo-level data, with built-in support for calibration using experimental data or prior knowledge. Meridian uses the No-U-Turn Sampler (NUTS) for Markov Chain Monte Carlo (MCMC) sampling to produce statistically rigorous results, and it includes GPU acceleration to significantly reduce computation time.
    Downloads: 6 This Week
    Last Update:
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  • 2
    Frappe

    Frappe

    Low code web framework for real world applications

    Frappe is a full-stack, low-code web framework written in Python and JavaScript, used to build scalable and modular enterprise applications. It powers ERPNext and includes tools for REST APIs, user management, document modeling, workflows, and real-time updates. Frappe uses a "model-view-controller" approach with its own ORM and frontend system, enabling rapid development without sacrificing control or performance.
    Downloads: 10 This Week
    Last Update:
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  • 3
    Marin

    Marin

    Framework for research and development of foundation models

    Marin is an open-source research platform and community for developing foundation models through transparent, reproducible experimentation. It covers the complete model-building pipeline from data curation and filtering through tokenization, pretraining, post-training, and evaluation. Experiments and decisions are documented as they occur, including unsuccessful approaches. The framework is primarily used for large language models but has also supported audio-text, DNA, and protein modeling research. Experiments are expressed as dependent steps that execute in topological order, enabling reproducible training workflows. ...
    Downloads: 0 This Week
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  • 4
    RAG Anything

    RAG Anything

    RAG-Anything: All-in-One RAG Framework

    RAG-Anything is an open-source unified framework that extends the Retrieval-Augmented Generation (RAG) paradigm to fully multimodal document and knowledge retrieval, enabling systems to ingest, parse, represent, and query rich content that includes text, images, tables, formulas, and other structured or visual elements. Traditional RAG systems are typically limited to text and cannot effectively work across heterogeneous document layouts, but RAG-Anything addresses this by modeling multimodal content in ways that preserve cross-modal relationships and semantic context, often treating content elements as interconnected knowledge entities rather than separate data silos. The system uses a multi-stage pipeline (e.g., document parsing, content analysis, knowledge graph construction, intelligent retrieval) so queries can navigate across modalities with deeper understanding and relevance.
    Downloads: 3 This Week
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  • 5
    Math tools in Python to tackle down problems in Operational Research fields. Comes with a Django based web interface to allow remote access to complex simulation means.
    Downloads: 0 This Week
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