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Examples include Amazon SageMaker Notebooks, [9] Google's Colab, [10] [11] and Microsoft's Azure Notebook. [12] Visual Studio Code supports local development of Jupyter notebooks. As of July 2022, the Jupyter extension for VS Code has been downloaded over 40 million times, making it the second-most popular extension in the VS Code Marketplace. [13]
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.
According to Stephen Wolfram: "The idea of a notebook is to have an interactive document that freely mixes code, results, graphics, text and everything else.", [4] and according to the Jupyter Project Documentation: "The notebook extends the console-based approach to interactive computing in a qualitatively new direction, providing a web-based ...
IPython continued to exist as a Python shell and kernel for Jupyter, but the notebook interface and other language-agnostic parts of IPython were moved under the Jupyter name. [ 11 ] [ 12 ] Jupyter is language agnostic and its name is a reference to core programming languages supported by Jupyter, which are Julia , Python , and R .
Creator Development started First public release Latest stable version Stable release date Cost () License Notes ADMB: David Fournier, ADMB Project
This page was last edited on 26 November 2021, at 16:57 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.
Anaconda is an open source [9] [10] data science and artificial intelligence distribution platform for Python and R programming languages.Developed by Anaconda, Inc., [11] an American company [1] founded in 2012, [11] the platform is used to develop and manage data science and AI projects. [9]
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]