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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.
Colab is a hosted Jupyter Notebook service that requires no setup to use and provides free access to computing resources, including GPUs and TPUs. Colab is especially well suited to machine learning, data science, and education.
WASM powered Jupyter running in the browser.
CoCalc supports many kernels right out of the box: several Python environments, SageMath, R Statistical Software Octave, Julia and many more. No software setup: 100% online. CoCalc is an online web service where you can run Jupyter notebooks right inside your browser.
WASM powered Jupyter running in the browser.
Write, execute, and visualize code collaboratively using the Jupyter Online Compiler. We offer real-time Jupyter Editor options. RunCode provides a Jupyter Notebooks online platform.
Our Jupyter Notebook environment offers an intuitive platform to create, analyze, and visualize data using Python, R, and more. Whether you're a data science enthusiast or a seasoned analyst, our interactive Jupyter Notebook is a powerful tool to practice data manipulation, perform statistical analysis, and develop data-driven insights.
Dec 15, 2023 · The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.
Jul 16, 2024 · The Jupyter Project offers an online training platform called “Try Jupyter” that allows users to get started with Python projects in Jupyter without having to install any software on their own computer.
Jul 13, 2021 · JupyterLite is a reboot of several attempts at making a full static Jupyter distribution that runs in the browser, without having to start the Python Jupyter Server on the host machine, usually done by running jupyter lab or jupyter notebook in a terminal.
