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MATLAB for Machine Learning

You're reading from MATLAB for Machine Learning

Product type Book

Published in Aug 2017

Publisher Packt

ISBN-13 9781788398435

Pages 382 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Authors (2):

Giuseppe Ciaburro

Pavan Kumar Kolluru

View More author details

Table of Contents (17) Chapters

Title Page

Credits

Foreword

About the Author

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. Getting Started with MATLAB Machine Learning

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

A neural network getting started GUI

A GUI is an interface that allows users to interact with computers through graphical icons and visual indicators instead of text-based interfaces. GUIs were introduced to make interactive operations more convenient in comparison to the more challenging procedures required by command-line interfaces, which require commands to be typed on a computer keyboard. The actions in a GUI are usually performed through direct manipulation of the graphical elements.

To make the application of neural networks as simple as possible, the toolbox gives us a series of GUIs. Seeing is believing. The main one is the nnstart() function, which opens a window with launch buttons for neural network fitting, pattern recognition, clustering, and time series tools:

>> nnstart

This command opens the Neural Network Start GUI, as shown in the following figure:

Figure 7.17: The Neural Network Start GUI

This GUI represents the dashboard of the entire toolbox, in the sense that, from...

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Authors (2)

Giuseppe Ciaburro

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).

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Pavan Kumar Kolluru

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