IPython Interactive Computing and Visualization Cookbook

Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform.

This course is equipped with several ready-to-use, focused recipes for high-performance scientific computing and data analysis to help you write better and faster code. You’ll be able to apply your learnings to various real-world examples, ranging from applied mathematics, scientific modeling, to machine learning. The course introduces you to effective programming techniques such as code quality and reproducibility, code optimization, and graphics card programming. You’ll also learn how to use different features of IPython and Jupyter Notebook in data science, signal and image processing, and applied mathematics.

By the end of this course, you’ll learn how to easily analyze and visualize all types of data in Jupyter Notebook.

About the Author

Cyrille Rossant, Ph.D., is a neuroscience researcher and software engineer at University College London. He is a graduate of École Normale Supérieure, Paris, where he studied mathematics and computer science. He has also worked at Princeton University and Collège de France. While working on data science and software engineering projects, he gained experience in numerical computing, parallel computing, and high-performance data visualization.

Fawaz Sammani has a first class degree in Mechatronics, Robotics and Automation engineering. He is a 2017, bronze medalist from International Conference on Robotics and Automation Sciences. He was also a second runner up for Infenion Week 2018, for the project on Development of Virtual Reality in Hospital.

He has been a course instructor with Udemy and freeCodeCamp. He currently is working as a Research assistant in a Multimedia University, Malaysia.