A Jupyter Notebook is an open source web application that allows data scientists to create and share documents that include live code, equations, and other multimedia resources.
Uses of Jupyter Notebook -
Jupyter notebooks are used for all sorts of data science tasks such as exploratory data analysis (EDA), data cleaning and transformation, data visualization, statistical modeling, machine learning, and deep learning.
Benefits of Using Jupyter Note Book-
Jupyter notebooks are especially useful for "showing the work" that your data team has done through a combination of code, markdown, links, and images. They are easy to use and can be run cell by cell to better understand what the code does.
Jupyter notebooks can also be converted to a number of standard output formats (HTML, Powerpoint, LaTeX, PDF, ReStructuredText, Markdown, Python) through the web interface. This flexibility makes it easy for data scientists to share their work with others.
How do Jupyter Notebooks work?
A Jupyter notebook has two components: a front-end web page and a back-end kernel. The front-end web page allows data scientists to enter programming code or text in rectangular "cells." The browser then passes the code to the back-end kernel which runs the code and returns the results.