Book Image

MATLAB for Machine Learning - Second Edition

By : Giuseppe Ciaburro
Book Image

MATLAB for Machine Learning - Second Edition

By: Giuseppe Ciaburro

Overview of 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.
Table of Contents (17 chapters)
Free Chapter
1
Part 1: Getting Started with Matlab
4
Part 2: Understanding Machine Learning Algorithms in MATLAB
9
Part 3: Machine Learning in Practice

Introducing image processing and computer vision

Through the five senses, humans gather information from the external world and process it, making decisions to carry out the actions that shape their daily lives. One of the most intriguing challenges in computer science is replicating this sequence of events, identifying and harnessing new sources of information. The ability to acquire and interpret information by simulating the human sensory system is called machine perception, and it is fundamental in the field of artificial intelligence.

Being able to interpret and acquire information from the external world is made possible through techniques such as encoding and information processing. Through digital image encoding techniques, it is possible to represent what humans can perceive in the form of bits. Depending on the methodologies used, it is possible to select the quantity and quality of the information to be represented. Through processing methods, on the other hand, it is...