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  1. GitHub is where over 100 million developers shape the future of software, together. Contribute to the open source community, manage your Git repositories, review code like a pro, track bugs and features, power your CI/CD and DevOps workflows, and secure code before you commit it.

  2. The open source community is the 💗 heart of GitHub and fundamental to how we build software today. See for yourself: GitHub Sponsors helped support more than 5k individuals and projects around the world 🌍

  3. GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.

  4. en.wikipedia.org › wiki › GitHubGitHub - Wikipedia

    It is commonly used to host open source software development projects. [8] As of January 2023, GitHub reported having over 100 million developers [9] and more than 420 million repositories, [10] including at least 28 million public repositories. [11] It is the world's largest source code host as of June 2023 .

  5. Learn how to start building, shipping, and maintaining software with GitHub. Explore our products, sign up for an account, and connect with the world's largest development community. Skip to main content

  6. Learn how you can use GitHub products to improve your software management process and collaborate with other people.

  7. You can find inspiration for your own projects and learning on GitHub and connect with a community. Downloading files from GitHub Learn how to download files from GitHub, and understand the difference between downloading, cloning, and forking.

  8. GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.

  9. Learn how to use GitHub with interactive courses designed for beginners and experts. Start with Introduction to GitHub.

  10. Git provides version control for scripts, metrics, data, and models. By using Git extension git-lfs, you can store and version a large database and machine learning models. In a typical data science project, you have a Jupyter notebook, dataset, model, metadata, and model metrics.

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