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MATLAB for Machine Learning: Practical examples of regression, clustering and neural networks Paperback – August 28, 2017

by Giuseppe Ciaburro (Author)

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Extract patterns and knowledge from your data in easy way using MATLAB

About This Book

Get your first steps into machine learning with the help of this easy-to-follow guide
Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB
Understand how your data works and identify hidden layers in the data with the power of machine learning.

Who This Book Is For

This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well.

What You Will Learn

Learn the introductory concepts of machine learning.
Discover different ways to transform data using SAS XPORT, import and export tools,
Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data.
Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment.
Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures.
Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox.
Learn feature selection and extraction for dimensionality reduction leading to improved performance.

In Detail

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.

Style and approach

The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.

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Editorial Reviews

About the Author

Giuseppe Ciaburro holds a master's degree in chemical engineering from Università degli Studi di Napoli Federico II, and a master's degree in acoustic and noise control from Seconda Università degli Studi di Napoli. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli".

He has over 15 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 Python and R, and he has extensive experience of working with MATLAB. An expert in acoustics and noise control, Giuseppe has wide experience in teaching professional computer courses (about 15 years), dealing with e-learning as an author. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He is currently researching machine learning applications in acoustics and noise control.

Product details

Paperback: 382 pages
Publisher: Packt Publishing - ebooks Account (August 28, 2017)
Language: English
ISBN-10: 1788398432
ISBN-13: 978-1788398435
Product Dimensions: 7.5 x 0.9 x 9.2 inches
Shipping Weight: 1.8 pounds (View shipping rates and policies)
Average Customer Review: 1 customer review
Amazon Best Sellers Rank: #1,228,955 in Books (See Top 100 in Books)
- #268 in Books > Computers & Technology > Computer Science > AI & Machine Learning > Machine Theory
- #1049 in Books > Computers & Technology > Databases & Big Data > Data Processing
- #1073 in Books > Computers & Technology > Computer Science > AI & Machine Learning > Intelligence & Semantics

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December 20, 2017

Format: Paperback

The author clearly has a very limited understanding of machine learning techniques and try to pay as less effort as possible to write this book.

The author's language is very redundant. There are a huge amount of paragraphs are directly copied from MATLAB official help document. Even worse, the code are full of errors as well as the results in this book.

I would recommend reading MATLAB's official help directly. Those are much better than this book!

Worst MATLAB book ever read. Do not buy it!!!

17 people found this helpful

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