Showing 5 open source projects for "job"

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  • Ship Agents Faster Icon
    Ship Agents Faster

    Transform your applications and workflows into powerful agentic systems at global scale.

    Gemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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  • $300 Free Credits for Your Google Cloud Projects Icon
    $300 Free Credits for Your Google Cloud Projects

    Start building on Google Cloud with $300 in free credits. No commitment, no credit card required until you're ready to scale.

    Launch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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  • 1
    Elyra

    Elyra

    Elyra extends JupyterLab with an AI centric approach

    Elyra is a set of AI-centric extensions to JupyterLab Notebooks. The Elyra Getting Started Guide includes more details on these features. A version-specific summary of new features is located on the releases page.
    Downloads: 7 This Week
    Last Update:
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  • 2
    SkyPilot

    SkyPilot

    SkyPilot: Run AI and batch jobs on any infra

    SkyPilot is a framework for running AI and batch workloads on any infra, offering unified execution, high cost savings, and high GPU availability. Run AI and batch jobs on any infra (Kubernetes or 12+ clouds). Get unified execution, cost savings, and high GPU availability via a simple interface.
    Downloads: 2 This Week
    Last Update:
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  • 3
    SageMaker Training Toolkit

    SageMaker Training Toolkit

    Train machine learning models within Docker containers

    Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and...
    Downloads: 8 This Week
    Last Update:
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  • 4
    Data Science Interviews

    Data Science Interviews

    Data science interview questions and answers

    Data Science Interviews is an open-source repository that collects common data science interview questions along with community-provided answers and explanations. The project serves as a preparation resource for students, job seekers, and professionals who want to review the technical knowledge required for data science roles. The repository organizes questions into different categories including theoretical machine learning concepts, technical programming questions, and probability or statistics problems. Many of the questions cover fundamental machine learning topics such as linear models, decision trees, neural networks, and evaluation metrics. ...
    Downloads: 0 This Week
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  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
    Start Free
  • 5
    FEDML Open Source

    FEDML Open Source

    The unified and scalable ML library for large-scale training

    ...Highly integrated with TensorOpera open source library, TensorOpera AI provides holistic support of three interconnected AI infrastructure layers: user-friendly MLOps, a well-managed scheduler, and high-performance ML libraries for running any AI jobs across GPU Clouds. A typical workflow is shown in the figure above. When a developer wants to run a pre-built job in Studio or Job Store, TensorOperaLaunch swiftly pairs AI jobs with the most economical GPU resources, and auto-provisions, and effortlessly runs the job, eliminating complex environment setup and management.
    Downloads: 0 This Week
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