Showing 28 open source projects for "g-code"

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    Spark Notebook

    Spark Notebook

    Interactive and Reactive Data Science using Scala and Spark

    Spark Notebook is an interactive web-based computational notebook designed to make working with Apache Spark more productive, exploratory, and expressive. It allows developers, data scientists, and analysts to write, run, and visualize Spark code in cells that support multiple languages such as Scala, Python, and SQL, all within the same notebook. Users can interleave runnable code, rich text markup, visualizations, equations, and results, enabling reproducible research and exploratory data analysis workflows. Because it runs on top of Spark’s distributed engine, it can scale from running locally on a laptop to executing on clusters with large datasets without changing user workflow. ...
    Downloads: 0 This Week
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  • 2
    Rodeo

    Rodeo

    A data science IDE for Python

    A data science IDE for Python. RODEO, that is an open-source python IDE and has been brought up by the folks at yhat, is a development environment that is lightweight, intuitive and yet customizable to its very core and also contains all the features mentioned above that were searched for so long. It is just like your very own personal home base for exploration and interpretation of data that aims at Data Scientists and answers the main question, "Is there anything like RStudio for Python?"...
    Downloads: 2 This Week
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  • 3
    Data Science Specialization

    Data Science Specialization

    Course materials for the Data Science Specialization on Coursera

    The Data Science Specialization Courses repository is a collection of materials that support the Johns Hopkins University Data Science Specialization on Coursera. It contains the source code and resources used throughout the specialization’s courses, covering a broad range of data science concepts and techniques. The repository is designed as a shared space for code examples, datasets, and instructional materials, helping learners follow along with lectures and assignments. It spans essential topics such as R programming, data cleaning, exploratory data analysis, statistical inference, regression models, machine learning, and practical data science projects. ...
    Downloads: 8 This Week
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