Showing 3 open source projects for "self code"

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    Skillfully - The future of skills based hiring

    Realistic Workplace Simulations that Show Applicant Skills in Action

    Skillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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  • The full-stack observability platform that protects your dataLayer, tags and conversion data Icon
    The full-stack observability platform that protects your dataLayer, tags and conversion data

    Stop losing revenue to bad data today. and protect your marketing data with Code-Cube.io.

    Code-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
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  • 1
    AI Researcher

    AI Researcher

    An autonomous AI researcher

    ...Through self-supervised feedback loops, agents adjust their strategies based on prior outcomes, improving both the quality and relevance of results over time.
    Downloads: 0 This Week
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  • 2
    Recommenders

    Recommenders

    Best practices on recommendation systems

    ...Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several state-of-the-art algorithms are included for self-study and customization in your own applications. Please see the setup guide for more details on setting up your machine locally, on a data science virtual machine (DSVM) or on Azure Databricks. Independent or incubating algorithms and utilities are candidates for the contrib folder. This will house contributions which may not easily fit into the core repository or need time to refactor or mature the code and add necessary tests.
    Downloads: 0 This Week
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  • 3
    Brain Tokyo Workshop

    Brain Tokyo Workshop

    Experiments and code from Google Brain’s Tokyo research workshop

    ...The repository includes implementations, experimental data, and supporting research papers that accompany published studies. Notable works such as Weight Agnostic Neural Networks and Neuroevolution of Self-Interpretable Agents highlight the team’s exploration of how AI can learn more efficiently and transparently. Overall, this repository serves as an open research hub for sharing ideas and advancing the understanding of intelligent systems.
    Downloads: 0 This Week
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