Book Image

MATLAB for Machine Learning

By : Giuseppe Ciaburro
Book Image

MATLAB for Machine Learning

By: Giuseppe Ciaburro

Overview of this book

MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You’ll start by getting your system ready with t he MATLAB environment for machine learning and you’ll see how to easily interact with the Matlab workspace. We’ll then move on to data cleansing, mining and analyzing various data types in machine learning and you’ll see how to display data values on a plot. Next, you’ll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You’ll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you’ll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB.
Table of Contents (17 chapters)
Title Page
About the Author
About the Reviewers
Customer Feedback
Improving the Performance of the Machine Learning Model - Dimensionality Reduction

About the Reviewers

Ankit Dixit is a data scientist and computer vision engineer from Mumbai, India; He has a B.Tech in biomedical engineering and a master's degree in computer vision specialization. He has been working in the field of computer vision and machine learning for more than 6 years.

He has worked with various software and hardware platforms for design and development of machine vision algorithms and has experience of machine learning algorithms such as decision trees, random forest, support vector machines, artificial neural networks, and deep neural networks. Currently, he is working on designing computer vision and machine learning algorithms for medical imaging data for Aditya Imaging and Information Technologies (part of Sun Pharmaceutical Advance Research Center), Mumbai. He does this with the use of advanced technologies such as ensemble methods and deep learning based models.

Ruben Oliva Ramos is a computer systems engineer with a master's degree in computer and electronic systems engineering, teleinformatics and networking, specialization from the University of Salle Bajio in Leon, Guanajuato, Mexico. He has more than 5 years of experience in developing web applications to control and monitor devices connected with Arduino and Raspberry Pi, and using web frameworks and cloud services to build the Internet of Things applications.

He is a mechatronics teacher at the University of Salle Bajio and teaches students of  the master's degree in design and engineering of mechatronics systems. Ruben also works at Centro de Bachillerato Tecnologico Industrial 225 in Leon, teaching subjects such as electronics, robotics and control, automation, and microcontrollers.

He is a technician, consultant, and developer of monitoring systems and datalogger data using technologies such as Android, iOS, Windows Phone, HTML5, PHP, CSS, Ajax, JavaScript, Angular, ASP .NET databases (SQlite, MongoDB, and MySQL), web servers, Node.js, IIS, hardware programming (Arduino, Raspberry Pi, Ethernet Shield, GPS, and GSM/GPRS), ESP8266, and control and monitor systems for data acquisition and programming.

He has written a book for Internet of Things Programming with JavaScript, Packt.

I would like to thank my savior and lord, Jesus Christ for giving me strength and courage to pursue this project, to my dearest wife, Mayte, our two lovely sons, Ruben and Dario, To my father (Ruben), my dearest mom (Rosalia), my brother (Juan Tomas), and my sister (Rosalia) whom I love, for all their support while reviewing this book, for allowing me to pursue my dream and tolerating not being with them after my busy day job.

Juan Tomás Oliva Ramos is an environmental engineer from the University of Guanajuato, with a master's degree in administrative engineering and quality. He has more than 5 years of experience in the management and development of patents, technological innovation projects, and the development of technological solutions through the statistical control of processes.

He is a teacher of statistics, entrepreneurship, and the technological development of projects since 2011.  He has always maintained an interest in the improvement and innovation in processes through technology. He became an entrepreneur mentor and technology management consultant, and started a new department of technology management and entrepreneurship at Instituto Tecnologico Superior de Purisima del Rincon.

He has worked on the book Wearable designs for Smart watches, Smart TV's and Android mobile devices. He has developed prototypes through programming and automation technologies for improvement of operations that have been registered for patents.

I want to thank God for giving me the wisdom and humility to review this book. I thank Rubén  for inviting me to collaborate on this adventure. I also thank my wife, Brenda, our two magic princesses, Regina and Renata, and our next member, Tadeo. All of you are my strength, happiness, and my desire to look for the best for you.







Prashant Verma started his IT career in 2011 as a Java developer at Ericsson, working in the telecoms domain. After a couple of years of Java EE experience, he moved into the big data domain, and has worked on almost all the popular big data technologies such as Hadoop, Spark, Flume, Mongo, Cassandra. He has also played with Scala. Currently, he works with QA Infotech as a lead data engineer, working on solving e-learning problems with analytics and machine learning.

Prashant has worked for many companies with domain knowledge of telecom and e-learning. He has also worked as a freelance consultant in his free time. He has worked as a reviewer on Spark For Java Developer.

I want to thank Packt Publishing for giving me the chance to review this book as well as my employer and my family for their patience while I was busy working on this book.