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MATLAB for Machine Learning - Second Edition

You're reading from MATLAB for Machine Learning - Second Edition

Product type Book

Published in Jan 2024

Publisher Packt

ISBN-13 9781835087695

Pages 374 pages

Edition 2nd Edition

Languages

Concepts

Machine Learning

Author (1):

Giuseppe Ciaburro

Table of Contents (17) Chapters

Preface

Part 1: Getting Started with Matlab

Chapter 1: Exploring MATLAB for Machine Learning

Chapter 2: Working with Data in MATLAB

Part 2: Understanding Machine Learning Algorithms in MATLAB

Chapter 3: Prediction Using Classification and Regression

Chapter 4: Clustering Analysis and Dimensionality Reduction

Chapter 5: Introducing Artificial Neural Network Modeling

Chapter 6: Deep Learning and Convolutional Neural Networks

Part 3: Machine Learning in Practice

Chapter 7: Natural Language Processing Using MATLAB

Chapter 8: MATLAB for Image Processing and Computer Vision

Chapter 9: Time Series Analysis and Forecasting with MATLAB

Chapter 10: MATLAB Tools for Recommender Systems

Chapter 11: Anomaly Detection in MATLAB

Index

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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...

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Authors (1)

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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