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Project Jupyter promotes open standards that third-party developers can leverage to build customized applications. Think HTML and CSS for interactive computing on the web.
Project Jupyter (/ ˈ dʒ uː p ɪ t ər / ⓘ) is a project to develop open-source software, open standards, and services for interactive computing across multiple programming languages. It was spun off from IPython in 2014 by Fernando Pérez and Brian Granger.
Project Jupyter builds tools, standards, and services for many different use cases. This page has links to interactive demos that allow you to try some our tools for free online, thanks to mybinder.org, a free public service provided by the Jupyter community.
Get up and running on your computer. Project Jupyter’s tools are available for installation via the Python Package Index, the leading repository of software created for the Python programming language. This page uses instructions with pip, the recommended installation tool for Python.
Welcome to the Project Jupyter documentation site. Jupyter is a large umbrella project that covers many different software offerings and tools, including the popular Jupyter Notebook and JupyterLab web-based notebook authoring and editing applications.
Jupyter Notebook is a notebook authoring application, under the Project Jupyter umbrella. Built on the power of the computational notebook format , Jupyter Notebook offers fast, interactive new ways to prototype and explain your code, explore and visualize your data, and share your ideas with others.
In this step-by-step Python tutorial, you learn how to get started with The Jupyter Notebook, an open source web application that you can use to create and share documents that contain live code, equations, visualizations, and text.
Jupyter Notebook is a simplified notebook authoring application, and is a part of Project Jupyter, a large umbrella project centered around the goal of providing tools (and standards) for interactive computing with computational notebooks.
The Jupyter Notebook is a web-based interactive computing platform that allows users to author data- and code-driven narratives that combine live code, equations, narrative text, visualizations, interactive dashboards and other media. Language of choice.
Jun 12, 2024 · I am happy to announce that Jupyter Docker Stacks project now provides GPU accelerated Docker images. This allows PyTorch or TensorFlow operations to use compatible NVIDIA GPUs for accelerated computation.
