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

Product type Paperback

Published in Aug 2017

Publisher Packt

ISBN-13 9781788398435

Length 382 pages

Edition 1st Edition

Languages

MATLAB

Tools

MATLAB

Concepts

Machine Learning

Authors (2):

Pavan Kumar Kolluru

Giuseppe Ciaburro

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Table of Contents (10) Chapters

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

What you need for this book

In this book, machine learning algorithms are implemented in the MATLAB environment. So, to reproduce the many examples in this book, you need a new version of MATLAB (R2017a recommended) and the following toolboxes: statistics and machine learning toolbox, neural network toolbox, and fuzzy logic toolbox.

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Authors (2)

Kolluru

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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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