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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

Familiarizing yourself with the MATLAB desktop

MATLAB is an interactive working environment based on the matrix, the most natural way to express computational mathematics. Moreover, it is a programming language designed for technical computing, mathematical analysis, and system simulation. The integrated graphics make it easy to view and acquire knowledge from the data. Finally, a large library of prebuilt toolboxes allows us to immediately start with programming.

After installing, to start MATLAB, simply double-click on the icon on the desktop; or from the system prompt, type matlab. At first startup, MATLAB will show us a desk of contents with all the necessary items for its proper and smooth operation. Figure 2.1 shows the MATLAB desktop in the R2017a version:

Figure 2.1: MATLAB R2017a desktop for Windows 10

The MATLAB desktop includes the following panels:

Current Folder: Shows the files that are stored in this folder (we can change it)
Command Window: At the prompt (>>), any MATLAB...

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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).

See other products by Giuseppe Ciaburro

Pavan Kumar Kolluru

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