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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.
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Python: Python: No No Yes No Yes Yes Yes Yes No Yes No [7] Deeplearning4j: Skymind engineering team; Deeplearning4j community; originally Adam Gibson 2014 Apache 2.0: Yes Linux, macOS, Windows, Android (Cross-platform) C++, Java: Java, Scala, Clojure, Python , Kotlin: Yes No [8] Yes [9] [10] No Computational Graph Yes [11] Yes Yes Yes Yes [12 ...
3.7 2019-03-25 Cross-platform: Python: Tkinter: PSFL: Yes Yes Yes No Unknown No No Yes No Yes Yes Unknown No No Komodo IDE: ActiveState: 10.2 2017-02-21 Cross-platform: Unknown Mozilla platform Proprietary: Yes Yes Yes Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Bazaar, CVS, Git, Mercurial ...
Google App Engine, a platform for developing and hosting web applications in Google-managed data centers, including Python. Grok, a web framework based on Zope Toolkit technology; Jam.py (web framework), a "full stack" WSGI rapid application development framework; Nevow, a web application framework originally developed by the company Divmod
The main editions also can take the form of one of the following special editions: N and KN editions The features in the N and KN Editions are the same as their equivalent full versions, but do not include Windows Media Player or other Windows Media-related technologies, such as Windows Media Center and Windows DVD Maker due to limitations set by the European Union and South Korea ...
TensorFlow is available on 64-bit Linux, macOS, Windows, and mobile computing platforms including Android and iOS. [citation needed] Its flexible architecture allows for easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices.
JAX is a machine learning framework for transforming numerical functions developed by Google with some contributions from Nvidia. [2] [3] [4] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and OpenXLA's XLA (Accelerated Linear Algebra).