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IPython Interactive Computing and Visualization Cookbook

You're reading from IPython Interactive Computing and Visualization Cookbook Over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science in the Jupyter Notebook

Product type Paperback

Published in Jan 2018

Publisher Packt

ISBN-13 9781785888632

Length 548 pages

Edition 2nd Edition

Languages

Python

Tools

IPython

Concepts

Data Analysis

Author (1):

Cyrille Rossant

View More author details

Table of Contents (19) Chapters

IPython Interactive Computing and Visualization CookbookSecond Edition

Contributors

Preface

1. A Tour of Interactive Computing with Jupyter and IPython FREE CHAPTER

2. Best Practices in Interactive Computing

3. Mastering the Jupyter Notebook

4. Profiling and Optimization

5. High-Performance Computing

6. Data Visualization

7. Statistical Data Analysis

8. Machine Learning

9. Numerical Optimization

10. Signal Processing

11. Image and Audio Processing

12. Deterministic Dynamical Systems

13. Stochastic Dynamical Systems

14. Graphs, Geometry, and Geographic Information Systems

15. Symbolic and Numerical Mathematics

Index

Chapter 2. Best Practices in Interactive Computing

In this chapter, we will cover the following topics:

Learning the basics of the Unix shell
Using the latest features of Python 3
Learning the basics of the distributed version control system Git
A typical workflow with Git branching
Efficient interactive computing workflows with IPython
Ten tips for conducting reproducible interactive computing experiments
Writing high-quality Python code
Writing unit tests with pytest
Debugging code with IPython

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Authors (1)

Cyrille Rossant

Cyrille Rossant

Cyrille Rossant, PhD, 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. He is the author of Learning IPython for Interactive Computing and Data Visualization, Second Edition, Packt Publishing.

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