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Project Jupyter's name is a reference to the three core programming languages supported by Jupyter, which are Julia, Python and R. Its name and logo are an homage to Galileo's discovery of the moons of Jupiter, as documented in notebooks attributed to Galileo. Jupyter is financially sponsored by NumFOCUS. [1]
It was developed by the Google Brain team for Google's internal use in research and production. [ 7 ] [ 8 ] [ 9 ] The initial version was released under the Apache License 2.0 in 2015. [ 1 ] [ 10 ] Google released an updated version, TensorFlow 2.0, in September 2019.
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.
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).
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
Google JAX: Google 2018 Apache License 2.0: Yes Linux, macOS, Windows: Python: Python: Only on Linux No Yes No Yes Yes Keras: François Chollet 2015 MIT license: Yes Linux, macOS, Windows: Python: Python, R: Only if using Theano as backend Can use Theano, Tensorflow or PlaidML as backends Yes No Yes Yes [20] Yes Yes No [21] Yes [22] Yes
Google Cloud Platform is a part [8] of Google Cloud, which includes the Google Cloud Platform public cloud infrastructure, as well as Google Workspace (G Suite), enterprise versions of Android and ChromeOS, and application programming interfaces (APIs) for machine learning and enterprise mapping services.
In 2021, Google revealed the physical layout of TPU v5 is being designed with the assistance of a novel application of deep reinforcement learning. [35] Google claims TPU v5 is nearly twice as fast as TPU v4, [36] and based on that and the relative performance of TPU v4 over A100, some speculate TPU v5 as being as fast as or faster than an H100 ...