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MATLAB for Machine Learning

You're reading from   MATLAB for Machine Learning Practical examples of regression, clustering and neural networks

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781788398435
Length 382 pages
Edition 1st Edition
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Authors (2):
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Pavan Kumar Kolluru Pavan Kumar Kolluru
Author Profile Icon Pavan Kumar Kolluru
Pavan Kumar Kolluru
Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Table of Contents (10) Chapters Close

Preface 1. Getting Started with MATLAB Machine Learning FREE CHAPTER 2. Importing and Organizing Data in MATLAB 3. From Data to Knowledge Discovery 4. Finding Relationships between Variables - Regression Techniques 5. Pattern Recognition through Classification Algorithms 6. Identifying Groups of Data Using Clustering Methods 7. Simulation of Human Thinking - Artificial Neural Networks 8. Improving the Performance of the Machine Learning Model - Dimensionality Reduction 9. Machine Learning in Practice

Working with media files

Images, videos, and audio files nowadays are an integral part of our lives. We use them widely thanks to the capabilities provided by modern devices that enable us to capture, store, and manipulate them. They often represent the input data we use in our machine learning applications, because through such algorithms, it is possible to extract a lot of information that at first glance is not so obvious. In this section, we will learn to deal with such files in the MATLAB environment.

Handling images

Raster images are made up of a grid of colored pixels. In MATLAB, images can be represented as two-dimensional matrices, where each matrix element corresponds to a single pixel of the displayed image. For...

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