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Learning SciPy for Numerical and Scientific Computing Second Edition
Learning SciPy for Numerical and Scientific Computing Second Edition

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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Learning SciPy for Numerical and Scientific Computing Second Edition

Chapter 1. Introduction to SciPy

There is no doubt that the labor of scientists in the twenty-first century is more comprehensive and interdisciplinary than in previous generations. Members of scientific communities connect in larger teams and work together on mission-oriented goals and across their fields. This paradigm on research is also reflected in the computational resources employed by researchers. No longer are researchers restricted to one type of commercial software, operating system, or vendor, but inspired by open source contributions made available and tested by research institutions and open source communities; research work often spans over various platforms and technologies.

This book presents the highly-recognized open source programming environment till date — a system based on two libraries of the computer language Python: NumPy and SciPy. In the following sections, we will guide you through examples from science and engineering on the usage of this system.

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Description

This book targets programmers and scientists who have basic Python knowledge and who are keen to perform scientific and numerical computations with SciPy.

Who is this book for?

This book targets programmers and scientists who have basic Python knowledge and who are keen to perform scientific and numerical computations with SciPy.

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

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Feb 26, 2015
Length: 188 pages
Edition : 2nd
Language : English
ISBN-13 : 9781783987719
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Product Details

Publication date : Feb 26, 2015
Length: 188 pages
Edition : 2nd
Language : English
ISBN-13 : 9781783987719
Category :
Languages :
Concepts :
Tools :

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Frequently bought together


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Total 95.97
Mastering Matplotlib
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€37.99
Learning SciPy for Numerical and Scientific Computing Second Edition
€24.99
Total 95.97 Stars icon

Table of Contents

9 Chapters
1. Introduction to SciPy Chevron down icon Chevron up icon
2. Working with the NumPy Array As a First Step to SciPy Chevron down icon Chevron up icon
3. SciPy for Linear Algebra Chevron down icon Chevron up icon
4. SciPy for Numerical Analysis Chevron down icon Chevron up icon
5. SciPy for Signal Processing Chevron down icon Chevron up icon
6. SciPy for Data Mining Chevron down icon Chevron up icon
7. SciPy for Computational Geometry Chevron down icon Chevron up icon
8. Interaction with Other Languages Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

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Full star icon Full star icon Full star icon Full star icon Half star icon 4.3
(10 Ratings)
5 star 40%
4 star 50%
3 star 10%
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Omphaloskepsis Oct 22, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
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 Amazon
Matteo May 06, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
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
Amazon Verified review Amazon
ABHIJIT Feb 28, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Very GOOD book. Must buy.
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JLai Apr 08, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
It is really helpful!
Amazon Verified review Amazon
Mihai Racovitan Apr 13, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
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.
Amazon Verified review Amazon
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