MATLAB for Machine Learning by Giuseppe Ciaburro

Key FeaturesGet your first steps into machine learning with the help of this easy-to-follow guideLearn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLABUnderstand how your data works and identify hidden layers in the data with the power of machine learning.Book DescriptionMATLAB 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.Youll start by getting your system ready with t he MATLAB environment for machine learning and youll see how to easily interact with the Matlab workspace. Well then move on to data cleansing, mining and analyzing various data types in machine learning and youll see how to display data values on a plot. Next, youll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions.Youll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, youll 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.What you will learnLearn 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.About the AuthorGiuseppe Ciaburro holds a masters degree in chemical engineering from Universita degli Studi di Napoli Federico II, and a masters degree in acoustic and noise control from Seconda Universita degli Studi di Napoli. He works at the Built Environment Control Laboratory - Universita 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.Table of ContentsGetting Started with Matlab Machine LearningImporting and organizing data in MatlabFrom data to knowledge discoveryFinding relationships between variables - Regression techniquesPattern recognition through classification algorithmsIdentifying groups of data by clustering methodsSimulation of human thinking - Artificial neural networksImproves the performance of the machine learning model - Dimensionality reductionMachine learning in practice