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IPython Interactive Computing and Visualization Cookbook

You're reading from   IPython Interactive Computing and Visualization Cookbook Harness IPython for powerful scientific computing and Python data visualization with this collection of more than 100 practical data science recipes

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Product type Paperback
Published in Sep 2014
Publisher
ISBN-13 9781783284818
Length 512 pages
Edition 1st Edition
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Author (1):
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Cyrille Rossant Cyrille Rossant
Author Profile Icon Cyrille Rossant
Cyrille Rossant
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Table of Contents (17) Chapters Close

Preface 1. A Tour of Interactive Computing with IPython FREE CHAPTER 2. Best Practices in Interactive Computing 3. Mastering the Notebook 4. Profiling and Optimization 5. High-performance Computing 6. Advanced 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 (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:

Being based on so many libraries, Sage is heavy and hard to compile from source. Binaries exist for most systems except Windows, where you generally have to use VirtualBox (a virtualization solution: www.virtualbox.org).

Alternatively, you can use Sage in a browser with an IPython notebook running on the cloud.

Note that...

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