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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 (17) Chapters

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

Getting started with Sage

Sage (http://www.sagemath.org) is a standalone mathematics software based on Python. It is an open source alternative to commercial products such as Mathematica, Maple, or MATLAB. Sage provides a unified interface to many open source mathematical libraries. These libraries include SciPy, SymPy, NetworkX, and other Python scientific packages, but also non-Python libraries such as ATLAS, BLAS, GSL, LAPACK, Singular, and many others.

In this recipe, we will give a brief introduction to Sage.

Getting ready

You can either:

Install Sage on your local computer (http://www.sagemath.org/doc/installation/)
Create Sage notebooks remotely in the cloud (https://cloud.sagemath.com/)

Being based on so many libraries, Sage is heavy and hard to compile from source. On Ubuntu, you can use the system's package manager (see http://www.sagemath.org/download-linux.html). Binaries exist for most systems except Windows, where you generally have to use VirtualBox (a virtualization solution...

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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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