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Data Science · Awesome GitHub Repositories

3 repos

Awesome GitHub RepositoriesData Science

Methodologies and computational resources used to perform advanced statistical modeling, predictive analysis, and scientific research on data.

Explore 3 awesome GitHub repositories matching data & databases · Data Science. Refine with filters or upvote what's useful.

  1. Home
  2. Data & Databases
  3. Data Analysis & Visualization
  4. Analytical Platforms and Engines
  5. Data Science

Awesome Data Science GitHub Repositories

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  • sindresorhus/awesome

    sindresorhus/awesome

    438,690GitHubView on GitHub↗

    This project is a community-curated knowledge base that organizes vast technical ecosystems into a hierarchical, human-readable directory. It serves as a comprehensive index of libraries, frameworks, and methodologies, designed to facilitate discovery and professional development across the entire spectrum of software

    awesomeawesome-listlists
  • jackfrued/Python-100-Days

    jackfrued/Python-100-Days

    178,734GitHubView on GitHub↗

    This project is a comprehensive, day-by-day curriculum designed to guide learners through the Python programming language and its professional applications. The content spans from fundamental syntax and object-oriented design to advanced topics including database management, web development, data analysis, and machine

    Jupyter Notebook
  • awesomedata/awesome-public-datasets

    awesomedata/awesome-public-datasets

    72,846GitHubView on GitHub↗

    This project is a community-maintained, open-access directory of high-quality public datasets. It serves as a centralized reference point for researchers, developers, and data scientists to locate reliable information sources across a wide spectrum of industries and scientific fields. By providing a structured index, t

    aaron-swartzawesome-public-datasetsdatasets

Explore sub-tags

  • Data Analysis FundamentalsCore concepts and toolsets for data analysts.
  • Data ChallengesCurated collections of datasets and problems designed for benchmarking and research.