Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, machine learning, and much more. This tutorial starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next you will learn to integrate the Jupyter system with different programming languages such as R, Python, JavaScript, and Julia; further, you'll explore the various versions and packages that are compatible with the Notebook system. Moving ahead, you'll master interactive widgets, namespaces, and working with Jupyter in multiuser mode. Towards the end, you will use Jupyter with a big dataset and will apply all the functionalities learned throughout the video.
About the Author
Dan Toomey has been developing applications for over 20 years. He has worked in a variety of industries and size companies in roles from sole contributor to VP/CTO level. For the last 10 years or so, he has been contracting to companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Again, as a contractor developer in the area. Dan has also written R for Data Sciences with Packt Publishing.
