Showing 6 open source projects for "workflow"

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  • 1
    targets

    targets

    Function-oriented Make-like declarative workflows for R

    ...It’s something like GNU Make for R, but more integrated. Skipping computation for up-to-date targets so that unchanged parts of the workflow are not recomputed. Targets can represent files or R objects, and tracking file changes etc is incorporated.
    Downloads: 0 This Week
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  • 2
    ClearML

    ClearML

    Streamline your ML workflow

    ...The ClearML Python Package for integrating ClearML into your existing scripts by adding just two lines of code, and optionally extending your experiments and other workflows with ClearML powerful and versatile set of classes and methods. The ClearML Server storing experiment, model, and workflow data, and supports the Web UI experiment manager, and ML-Ops automation for reproducibility and tuning. It is available as a hosted service and open source for you to deploy your own ClearML Server. The ClearML Agent for ML-Ops orchestration, experiment and workflow reproducibility, and scalability.
    Downloads: 0 This Week
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  • 3
    AWS SDK for pandas

    AWS SDK for pandas

    Easy integration with Athena, Glue, Redshift, Timestream, Neptune

    ...It also supports Redshift, OpenSearch, and other services, enabling ETL tasks that blend SQL engines and Python transformations. Operational helpers handle IAM, sessions, and concurrency while exposing knobs for encryption, versioning, and catalog consistency. The result is a productive workflow that keeps your analytics in Python while leveraging AWS-native storage and query engines at scale.
    Downloads: 0 This Week
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  • 4
    Data Science Notes

    Data Science Notes

    Curated collection of data science learning materials

    Data Science Notes is a large, curated collection of data science learning materials, with explanations, code snippets, and structured notes across the typical end-to-end workflow. It spans foundational math and statistics through data wrangling, visualization, machine learning, and practical project organization. The content emphasizes hands-on understanding by pairing narrative notes with runnable examples, making it useful for both self-study and classroom settings. Because it aggregates topics in one place, learners can move linearly or jump into specific areas as needed during projects. ...
    Downloads: 0 This Week
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  • 5
    Data Science at the Command Line

    Data Science at the Command Line

    Data science at the command line

    ...You’ll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you’re comfortable processing data with Python or R, you’ll learn how to greatly improve your data science workflow by leveraging the command line’s power.
    Downloads: 1 This Week
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  • 6
    Data Science Specialization

    Data Science Specialization

    Course materials for the Data Science Specialization on Coursera

    ...By providing centralized resources, the repo makes it easier for students to practice concepts and replicate examples from the curriculum. It also offers a structured view of how multiple disciplines—programming, statistics, and applied data analysis—come together in a professional workflow.
    Downloads: 3 This Week
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