Showing 133 open source projects for "data quality"

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  • 1
    SAIM allows to interlink knowledge bases in the Semantic Web. It focuses on instance matching of very large knowledge bases available as SPARQL endpoints. SAIM uses machine learning techniques and is compatible with SILK.
    Downloads: 0 This Week
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  • 2
    JNOMO is a Jean Plugin for providing more expresiveness in its rule language. This plugin allows for retracting or priorizing rules, removing facts as a rule consecuence or even asking for the "unspecified" information into Knowledge Base.
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  • 3
    WebAPSEE - Flexible Process Management
    WebAPSEE is an open source project which aims to provide automated support for software process management. The users list is: http://groups.google.com/group/webapsee-usuarios
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  • 4
    The Introspector enables the programming tools that deal with source code such as the compiler to communicate in a standard and neutral manner reducing the accidental cost of programming. http://github.com/h4ck3rm1k3/
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  • 5
    This is a C++ Neural Network controller developed under Linux. This controller abstracts a reletionship between inputs and outputs. The data used are in text format. New neuron types are needed and a graphic interface. www.unipd.it/~akela2/project
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  • 6
    Multilayered feed-forward neural network software written in C++. Backpropagation and RPROP are available as training algorithms. Design goals: speed of execution when calculating the output to new data, and quality of training (preprocessing: PCA).
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  • 7
    lastest

    lastest

    AI-supported visual verification and tests you can actually trust.

    Lastest.cloud is a free, open-source verification of development, self-hosted visual regression and end-to-end testing platform for web applications. An AI agent records you clicking through your running app and generates Playwright tests with multi-selector fallback. Replays are deterministic and token-free, so your CI/CD bill doesn't scale with your test suite. Lastest ships three diff engines side-by-side — pixel (pixelmatch), structural (SSIM), and perceptual (Butteraugli) — so...
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  • 8
    GigaChat 3 Ultra

    GigaChat 3 Ultra

    High-performance MoE model with MLA, MTP, and multilingual reasoning

    ...Its training corpus incorporates ten languages, enriched with books, academic sources, code datasets, mathematical tasks, and more than 5.5 trillion tokens of high-quality synthetic data. This combination significantly boosts reasoning, coding, and multilingual performance across modern benchmarks. Designed for high-performance deployment, GigaChat 3 Ultra supports major inference engines and offers optimized BF16 and FP8 execution paths for cluster-grade hardware.
    Downloads: 0 This Week
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