Showing 7 open source projects for "drift"

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  • 1
    NannyML

    NannyML

    Detecting silent model failure. NannyML estimates performance

    NannyML is an open-source python library that allows you to estimate post-deployment model performance (without access to targets), detect data drift, and intelligently link data drift alerts back to changes in model performance. Built for data scientists, NannyML has an easy-to-use interface, and interactive visualizations, is completely model-agnostic, and currently supports all tabular classification use cases. NannyML closes the loop with performance monitoring and post deployment data science, empowering data scientist to quickly understand and automatically detect silent model failure. ...
    Downloads: 9 This Week
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  • 2
    whylogs

    whylogs

    The open standard for data logging

    whylogs is an open-source library for logging any kind of data. With whylogs, users are able to generate summaries of their datasets (called whylogs profiles) which they can use to track changes in their dataset Create data constraints to know whether their data looks the way it should. Quickly visualize key summary statistics about their datasets. whylogs profiles are the core of the whylogs library. They capture key statistical properties of data, such as the distribution (far beyond...
    Downloads: 4 This Week
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  • 3
    Arize Phoenix

    Arize Phoenix

    Uncover insights, surface problems, monitor, and fine tune your LLM

    Phoenix provides ML insights at lightning speed with zero-config observability for model drift, performance, and data quality. Phoenix is an Open Source ML Observability library designed for the Notebook. The toolset is designed to ingest model inference data for LLMs, CV, NLP and tabular datasets. It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve.
    Downloads: 0 This Week
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  • 4
    WhyLogs Java Library

    WhyLogs Java Library

    Profile and monitor your ML data pipeline end-to-end

    This is a Java implementation of WhyLogs, with support for Apache Spark integration for large scale datasets. Understanding the properties of data as it moves through applications is essential to keeping your ML/AI pipeline stable and improving your user experience, whether your pipeline is built for production or experimentation. WhyLogs is an open source statistical logging library that allows data science and ML teams to effortlessly profile ML/AI pipelines and applications, producing log...
    Downloads: 0 This Week
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  • 5
    SpacePy
    Now maintained at github.com/spacepy/spacepy Space Science library for Python - contains superposed epoch classes, drift shell tracing, access to magnetic field models, streamline tracing, bootstrap confidence limits, time and coordinate conversions, etc.
    Downloads: 0 This Week
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  • 6
    arrowmatcher
    Arrowmatcher is a ballistics software for crossbow archers. It can calculate the speed, kinetic energy, trajectory, aiming solution and much more of an arrow (or bullet). It uses a simplified 6 degree of freedom model.
    Downloads: 1 This Week
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  • 7
    Genealogy of Life
    Controversial ideas of Williamson, Margulis & others suggest speciation by hybridizing might be more common than originally thought. Taking this concept to the nth degree & assuming that indeed, speciation mostly occurs by hybridizing events, not the accumulation of mutations or genetic drift, here is a catalogueoflife2gedcom converter. It allows the tree of life to be displayed as a human genealogy tree with hybridizing events depicted as "marriages." The idea then is that mutation accrual & genetic drift are the determining factors for "species maturation," not speciation itself. Unfortunately the Catalogue of Life Project, catalogueoflife.org, changed its database format more recently, so this converter only works on older versions of the data. ...
    Downloads: 0 This Week
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