Gnu Octave by Example: A Fast and Practical Approach to Learning Gnu Octave di Ashwin Pajankar, Sharvani Chandu edito da APRESS
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Gnu Octave by Example: A Fast and Practical Approach to Learning Gnu Octave

A Fast and Practical Approach to Learning GNU Octave

Editore:

APRESS

EAN:

9781484260852

ISBN:

1484260856

Pagine:
145
Formato:
Paperback
Lingua:
Inglese
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Descrizione Gnu Octave by Example: A Fast and Practical Approach to Learning Gnu Octave

Get a quick start to learn, understand, and apply GNU Octave using a math- and programming-friendly approach. This book focuses on an end-to-end track to teach mathematical programming, data science, signal processing, and image processing with GNU Octave. GNU Octave by Example starts with an introduction to GNU Octave, a free and open-source alternative to MATLAB. Next, it explains the processes to install GNU Octave on popular operating systems such as Windows, Ubuntu, Raspberry Pi, and other platforms. Further, it covers hands-on exercises with GNU Octave exploring the basic functionality and command line in interactive mode. This is followed by covering matrices and various operations including how to read and analyze data from various sources. Moving forward, it introduces commonly used programming constructs in data visualization. It explains 2D and 3D data visualization along with data analysis. It also demonstrates the concepts related to geometry and its application with GNU Octave. It concludes with coverage of signal processing followed by image, video, and audio processing techniques. After reading this book, you will be able to write your own programs for scientific and numerical applications. What You Will Learn ¿ Understand the practical aspects of GNU Octave with math and programming-friendly abstractions ¿ Install GNU Octave on multiple platforms including Windows, Raspberry Pi, and Ubuntu ¿ Work with GNU Octave using the GUI, the command line, and Jupyter notebooks ¿ Implement 2D and 3D data visualization and analysis with GNU Octave Who This Book Is For Software engineers, data engineers, data science enthusiasts, and computer vision professionals.

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