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Numpy Beginner's Guide (Update)

You're reading from   Numpy Beginner's Guide (Update) Build efficient, high-speed programs using the high-performance NumPy mathematical library

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Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781785281969
Length 348 pages
Edition 1st Edition
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Table of Contents (16) Chapters Close

Preface 1. NumPy Quick Start FREE CHAPTER 2. Beginning with NumPy Fundamentals 3. Getting Familiar with Commonly Used Functions 4. Convenience Functions for Your Convenience 5. Working with Matrices and ufuncs 6. Moving Further with NumPy Modules 7. Peeking into Special Routines 8. Assuring Quality with Testing 9. Plotting with matplotlib 10. When NumPy Is Not Enough – SciPy and Beyond 11. Playing with Pygame A. Pop Quiz Answers B. Additional Online Resources C. NumPy Functions' References
Index

Artificial Intelligence

Often we need to mimic intelligent behavior within a game. The scikit-learn project aims to provide an API for machine learning, and what I like most about it is its amazing documentation. We can install scikit-learn with the package manager of our operating system, though this option may or may not be available, depending on your operating system, but should be the most convenient route. Windows users can just download an installer from the project website. On Debian and Ubuntu, the project is called python-sklearn. On MacPorts, the ports are called py26-scikits-learn and py27-scikits-learn. We can also install from source or using easy_install. There are third-party distributions from Python(x,y), Enthought, and NetBSD.

We can install scikit-learn by typing at command line:

$ [sudo] pip install -U scikit-learn

We can also type the following instead of the preceding line:

$ [sudo] easy_install -U scikit-learn

This may not work because of permissions, so you might...

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