Easy to share: Jupyter Notebooks are saved in the structured text files (JSON format), which makes them easily shareable.

It also uses online tools and nbviewer which allows you to render a publicly available notebook in the browser directly. Easy to convert: Jupyter Notebook allows users to convert the notebooks into other formats such as HTML and PDF.All in one place: As you know, Jupyter Notebook is an open-source web-based interactive environment that combines code, text, images, videos, mathematical equations, plots, maps, graphical user interface and widgets to a single document.There are the following advantages of Jupyter Notebook. Creating a Notebook in Jupyter Notebook.In this tutorial, we are going to discuss the following topics: Note: Jupyter Notebook mainly used for Python because Python is used with Artificial Intelligence (AI), Machine learning, as well as Deep learning. It integrates with many programming languages like Python, PHP, R, C#, etc. Jupyter Notebook is an open-source, web-based interactive environment, which allows you to create and share documents that contain live code, mathematical equations, graphics, maps, plots, visualizations, and narrative text. Our Jupyter Notebook tutorial is designed for beginners and professionals. He maintains and contributes to JupyterLab, JupyterLab Desktop and several other projects in the Jupyter eco-system.Jupyter Notebook tutorial provides basic and advanced concepts of the Jupyter Notebook. Mehmet Bektas is a Senior Software Engineer at Netflix and a Jupyter Core Developer. Please provide your valuable input using project’s GitHub issues or by other available channels. We are looking forward to user feedback from the community to define project’s roadmap. Follow the project on GitHub and Jupyter Blog for updates. This release updates and modernizes the JupyterLab App after couple of years from the initial release and forms a new baseline for the new features to be built-on. Libraries included in the environment are numpy, scipy, pandas, ipywidgets and matplotlib. The backend of the JupyterLab along with Python libraries are provided via a bundled conda Python environment. JupyterLab App is based on Electron and it runs the front-end of JupyterLab inside an embedded browser. One-click installer on macOS Built-in Python environment

Jupyter notebook windows