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  2. pip (package manager) - Wikipedia

    en.wikipedia.org/wiki/Pip_(package_manager)

    pip (also known by Python 3's alias pip3) is a package-management system written in Python and is used to install and manage software packages. [4] The Python Software Foundation recommends using pip for installing Python applications and its dependencies during deployment. [5] Pip connects to an online repository of public packages, called the ...

  3. XGBoost - Wikipedia

    en.wikipedia.org/wiki/XGBoost

    Soon after, the Python and R packages were built, and XGBoost now has package implementations for Java, Scala, Julia, Perl, and other languages. This brought the library to more developers and contributed to its popularity among the Kaggle community, where it has been used for a large number of competitions. [11]

  4. CatBoost - Wikipedia

    en.wikipedia.org/wiki/Catboost

    It works on Linux, Windows, macOS, and is available in Python, [8] R, [9] and models built using CatBoost can be used for predictions in C++, Java, [10] C#, Rust, Core ML, ONNX, and PMML. The source code is licensed under Apache License and available on GitHub. [6] InfoWorld magazine awarded the library "The best machine learning tools" in 2017.

  5. Kaggle - Wikipedia

    en.wikipedia.org/wiki/Kaggle

    Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.

  6. Python Package Index - Wikipedia

    en.wikipedia.org/wiki/Python_Package_Index

    The Python Distribution Utilities (distutils) Python module was first added to the Python standard library in the 1.6.1 release, in September 2000, and in the 2.0 release, in October 2000, nine years after the first Python release in February 1991, with the goal of simplifying the process of installing third-party Python packages.

  7. CuPy - Wikipedia

    en.wikipedia.org/wiki/CuPy

    CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3]

  8. List of free and open-source software packages - Wikipedia

    en.wikipedia.org/wiki/List_of_free_and_open...

    This is a list of free and open-source software packages , computer software licensed under free software licenses and open-source licenses. Software that fits the Free Software Definition may be more appropriately called free software ; the GNU project in particular objects to their works being referred to as open-source . [ 1 ]

  9. Conda (package manager) - Wikipedia

    en.wikipedia.org/wiki/Conda_(Package_Manager)

    Conda is an open-source, [2] cross-platform, [3] language-agnostic package manager and environment management system. It was originally developed to solve package management challenges faced by Python data scientists, and today is a popular package manager for Python and R.