Scipy Lecture Notes: One document to learn numerics, science, and data with Python

Scipy Lecture Notes: One document to learn numerics, science, and data with Python

A self-contained introduction to everything that is needed to use Python for science, from the language itself, to numerical computing or plotting.

Publication date: 31 Dec 2015

ISBN-10: n/a

ISBN-13: n/a

Paperback: 363 pages

Views: 3,932

Type: Lecture Notes

Publisher: n/a

License: Creative Commons Attribution 4.0 International

Post time: 28 May 2016 11:00:00

Scipy Lecture Notes: One document to learn numerics, science, and data with Python

Scipy Lecture Notes: One document to learn numerics, science, and data with Python A self-contained introduction to everything that is needed to use Python for science, from the language itself, to numerical computing or plotting.
Tag(s): Computer Aided Mathematics Python Statistics
Publication date: 31 Dec 2015
ISBN-10: n/a
ISBN-13: n/a
Paperback: 363 pages
Views: 3,932
Document Type: Lecture Notes
Publisher: n/a
License: Creative Commons Attribution 4.0 International
Post time: 28 May 2016 11:00:00
Summary/Excerpts of (and not a substitute for) the Creative Commons Attribution 4.0 International:
You are free to:

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About the Notes:

Tutorials on the scientific Python ecosystem: a quick introduction to central tools and techniques. The different chapters each correspond to a 1 to 2 hours course with increasing level of expertise, from beginner to expert.

Table of Contents:

Scientific computing with tools and workflow - The Python language - NumPy: creating and manipulating numerical data - Matplotlib: plotting - Scipy : high-level scientific computing - Getting help and finding documentation - Advanced Python Constructs - Advanced Numpy - Debugging code - Optimizing code - Sparse Matrices in SciPy - Image manipulation and processing using Numpy and Scipy - Mathematical optimization: finding minima of functions - Interfacing with C - Statistics in Python - Sympy : Symbolic Mathematics in Python - Scikit-image: image processing - Traits: building interactive dialogs - 3D plotting with Mayavi - scikit-learn: machine learning in Python.




About The Editor(s)


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Emmanuelle Gouillart

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Olav Vahtras

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Gaël Varoquaux

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