Home Data MATLAB for Machine Learning - Second Edition

MATLAB for Machine Learning - Second Edition

By Giuseppe Ciaburro
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Customised display settings for better reading experience
50+ new titles added every month on new and emerging tech
Playlists, Notes and Bookmarks to easily manage your learning
Mobile App with offline access
What do you get with eBook?
Download this book in EPUB and PDF formats
Access this title in our online reader
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Online reader with customised display settings for better reading experience
What do you get with video?
Download this video in MP4 format
Access this title in our online reader
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What do you get with video?
Stream this video
Access this title in our online reader
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  1. Free Chapter
    Part 1: Getting Started with Matlab
About this book
Discover why the MATLAB programming environment is highly favored by researchers and math experts for machine learning with this guide which is designed to enhance your proficiency in both machine learning and deep learning using MATLAB, paving the way for advanced applications. By navigating the versatile machine learning tools in the MATLAB environment, you’ll learn how to seamlessly interact with the workspace. You’ll then move on to data cleansing, data mining, and analyzing various types of data in machine learning, and visualize data values on a graph. As you progress, you’ll explore various classification and regression techniques, skillfully applying them with MATLAB functions. This book teaches you the essentials of neural networks, guiding you through data fitting, pattern recognition, and cluster analysis. You’ll also explore feature selection and extraction techniques for performance improvement through dimensionality reduction. Finally, you’ll leverage MATLAB tools for deep learning and managing convolutional neural networks. By the end of the book, you’ll be able to put it all together by applying major machine learning algorithms in real-world scenarios.
Publication date:
January 2024
Publisher
Packt
Pages
374
ISBN
9781835087695

 

Part 1: Getting Started with Matlab

This part provides background information and essential knowledge about MATLAB tools, along with an introduction to basic machine learning concepts. We also will focus on importing and organizing data in MATLAB, emphasizing familiarity with the MATLAB workspace for simplicity in operations. The discussion covers analyzing various data formats, moving data in and out of MATLAB, exploring datatypes for grouping variables and categorical data, exporting data in different formats such as cell arrays, structure arrays, and tabular data, and saving it in MATLAB-supported file formats. The ultimate goal is to prepare data in the right format for the subsequent phase of data analysis.

This part has the following chapters:

About the Author
  • 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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MATLAB for Machine Learning - Second Edition
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