Showing 4 open source projects for "lotto prediction algorithm"

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    NannyML

    NannyML

    Detecting silent model failure. NannyML estimates performance

    ...By using NannyML, data scientists can finally maintain complete visibility and trust in their deployed machine learning models. When the actual outcome of your deployed prediction models is delayed, or even when post-deployment target labels are completely absent, you can use NannyML's CBPE-algorithm to estimate model performance.
    Downloads: 0 This Week
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  • 2
    Machine Learning From Scratch

    Machine Learning From Scratch

    Bare bones NumPy implementations of machine learning models

    ML-From-Scratch is an open-source machine learning project that demonstrates how to implement common machine learning algorithms using only basic Python and NumPy rather than relying on high-level frameworks. The goal of the project is to help learners understand how machine learning algorithms work internally by building them step by step from fundamental mathematical operations. The repository includes implementations of algorithms ranging from simple models such as linear regression and...
    Downloads: 2 This Week
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  • 3
    ExSTraCS

    ExSTraCS

    Extended Supervised Tracking and Classifying System

    This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces.
    Downloads: 0 This Week
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  • 4
    This project applies an interpretation of a k-NN algorithm to a library of GPS commuter data for speed prediction. The overall goal is to lay the foundation for a power management protocol for use in electric vehicles with hybrid energy storage.
    Downloads: 0 This Week
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