Showing 4 open source projects for "data quality"

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  • 1
    Cookiecutter Data Science

    Cookiecutter Data Science

    Project structure for doing and sharing data science work

    A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. When we think about data analysis, we often think just about the resulting reports, insights, or visualizations. While these end products are generally the main event, it's easy to focus on making the products look nice and ignore the quality of the code that generates them. Because these end products are created programmatically, code quality is still important! ...
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  • 2
    tsfresh

    tsfresh

    Automatic extraction of relevant features from time series

    tsfresh is a python package. It automatically calculates a large number of time series characteristics, the so called features. tsfresh is used to to extract characteristics from time series. Without tsfresh, you would have to calculate all characteristics by hand. With tsfresh this process is automated and all your features can be calculated automatically. Further tsfresh is compatible with pythons pandas and scikit-learn APIs, two important packages for Data Science endeavours in python....
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  • 3
    AWA-Core

    AWA-Core

    Full application for factory, process engineer and Automation..

    IT'S HERE-----FINALLY. AWA-Core 2026 is here with a totally new architecture. The core is now in Client/Server architecture and open to other applications (including yours). New interfaces for the server and client sides. Please, go to our youTube channel to see many tutorials about this new release. Don't waste your time trying things and clicking everywhere. Wait for our tutorials, install AWA-Core on a single PC or in a complete C/S architecture (Servers provided) and run...
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  • 4
    Self-learning-Computer-Science

    Self-learning-Computer-Science

    Resources to learn computer science in your spare time

    Self-learning Computer Science is a curated, open-source guide repository designed to help learners independently study computer science topics using high-quality university-level resources. The author (an undergraduate CS student) assembled links to courses from institutions like MIT, UC Berkeley, Stanford, etc., covering mathematics, programming, data structures/algorithms, computer architecture, machine learning, software engineering and more. It’s aimed at learners who find traditional course structures restrictive and want a flexible, self-paced path through CS, with a focus on building depth and breadth rather than shortcut exam skills. ...
    Downloads: 0 This Week
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