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What you will learn

Get to know the benefits of using the combination of Python, NumPy, SciPy, and matplotlib as a programming environment for scientific purposes

Create and manipulate an object array used by SciPy

Use SciPy with large matrices to compute eigenvalues and eigenvectors

Focus on construction, acquisition, quality improvement, compression, and feature extraction of signals

Make use of SciPy to collect, organize, analyze, and interpret data, with examples taken from statistics and clustering

Acquire the skill of constructing a triangulation of points, convex hulls, Voronoi diagrams, and many similar applications

Find out ways that SciPy can be used with other languages such as C/C++, Fortran, and MATLAB/Octave

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

Frequently bought together

$43.99

$49.99

Learning SciPy for Numerical and Scientific Computing Second Edition

$32.99

Total $ 126.97

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Amazon verified reviews

Omphaloskepsis Oct 22, 2016

its good if your a novice at using numpy, scipy, matplot;ib, etc . Not worth it if you use scypi all the time as I do , but still worth 5 stars if your just getitng started.

Amazon Verified review

Matteo May 06, 2015

This book provide a very good starting point to start using scipy for scientific computing. The book start with a basic python training and then continues with scipy proper. Exercises are sorta complex but given the topic it's no big deal. If you need to start using scipy for any or your project or you need to pick a language to help with your math studies this book is for you

ABHIJIT Feb 28, 2019

Very GOOD book. Must buy.

JLai Apr 08, 2016

It is really helpful!

Mihai Racovitan Apr 13, 2015

I bought an electronic version of this book directly from Packt Publishing at an incredible price. I use Python constantly, so I was curious what this book can provide. Three authors with experience in the architectures of high-performance number crunching with Python combined their experience into writing this book, so they offer quite a few valuable gems in writing code. The code is also available when you buy the electronic version. You do not need to be an advanced Python user since this book is written in an elegant combination of introducing the basics with presenting the challenges that may arise from using SciPy. For this reason is probably not recommended for high-level Python users which should be probably quite accustomed with the code written in this book.

Learning SciPy for Numerical and Scientific Computing Second Edition: Quick solutions to complex numerical problems in physics, applied mathematics, and science with SciPy , Second Edition

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