Data science and scientific computing are privileged to have an amazing interactive tool called Jupyter Notebook. With Jupyter Notebook, you can write and run code in an interactive web environment that also has the capability to have visualizations, images, and videos. It makes the testing of equations and prototyping a lot easier, has the support of over 40 programming languages, and is completely open source.
GitHub supports Jupyter Notebooks (static). A Notebook with a record of computation can be shared through the Jupyter Notebook viewer or other cloud storage. Jupyter Notebooks are extensively used for coding machine-learning algorithms, statistical modeling and numerical simulation, and data munging. Jupyter ...
