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Interactive Computing with Jupyter Notebook [Video]

This is the code repository for Interactive Computing with Jupyter Notebook [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.

About the Video Course

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.

Interactive Computing with Jupyter Notebook, contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. This course covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming.

In short, you will master relatively advanced methods in interactive numerical computing, high-performance computing, and data visualization.

What You Will Learn

Instructions and Navigation

Assumed Knowledge

To fully benefit from the coverage included in this course, you will need:
This course is intended for anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, and hobbyists. A basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.

Technical Requirements

This course has the following software requirements:
IPython console, Jupyter Notebook, Graphic Card - NVIDIA GeForce GT 710, Operating System - Windows 7+/ubuntu 16.04.

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