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

Summary

In this chapter, we understood the basic concepts surrounding computer vision and how to implement a model for object recognition using MATLAB. We started by introducing image processing and computer vision. We learned how tools are available to process images and how computer vision is used for object recognition, motion detection, and pattern recognition. Then, we explored MATLAB tools for computer vision, and how the capabilities and functions provided by MATLAB create a robust environment for the development and prototyping of computer vision applications. Whether your focus is on tasks such as image analysis, object detection, 3D reconstruction, or any related application, MATLAB offers the necessary tools and features to support your work effectively.

After that, we learned how to build a MATLAB model for object recognition by using a CNN and the MNIST dataset. We understood how to import image data into a MATLAB workspace and how to use images to train a CNN. Then...