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Openlayer

Test, fix, and improve your ML models. We were ML engineers experiencing the struggle that goes into properly evaluating models, making them robust to the myriad of unexpected edge cases they encounter in production, and understanding the reasons behind their mistakes.

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  1. Open-source toolkit for ML model evaluation and active learning

    github.com

    The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.

    Hacker News11점

  2. Python library to scan ML models for vulnerabilities

    docs.giskard.ai

    I’ve been working on this automatic scanner for ML models to detect issues like underperforming data slices, overconfidence in predictions, robustness problems, and others.

    Hacker News20점

  3. Compile ML models into dependency-free source code for easy deployment

    waveworks.dk

    I'm a machine learning engineer who always found it annoying to integrate ML models into phone apps, smartwatch apps, microcontroller firmware etc...

    Hacker News37점

  4. Smolmodels

    github.com

    open-source tool to build ML models using natural language

    Hacker News37점

  5. Open-Sourcing Google's Lattice Models in PyTorch

    github.com

    A PyTorch implementation of constrained optimization and modeling techniques

    Hacker News13점