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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

Polynomials

Do you like calculus? Well I love it! One of the ideas in calculus is Taylor expansion, that is, representing a differentiable function as an infinite series (see https://www.khanacademy.org/math/integral-calculus/sequences_series_approx_calc/taylor-series/v/generalized-taylor-series-approximation and http://en.wikipedia.org/wiki/Taylor_series.).

Note

The Taylor series is defined as the following sum:

Polynomials
Polynomials

in this definition is the nth derivative of the function f computed at the point a.

In practice, this means that we can estimate any differentiable, and therefore continuous, function with a polynomial of a high degree. We would then assume that the terms of the higher degrees are negligibly small.

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