MATLAB for Machine Learning

£29.99

MATLAB for Machine Learning

Unlock the power of deep learning for swift and enhanced results

Computer science Artificial intelligence Natural language and machine translation

Author: Giuseppe Ciaburro

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Language: English

Published by: De Gruyter

Published on: 13th February 2024

Format: LCP-protected ePub

ISBN: 9781835089538


Key Features

Work with the MATLAB Machine Learning Toolbox to implement a variety of machine learning algorithms

Evaluate, deploy, and operationalize your custom models, incorporating bias detection and pipeline monitoring

Uncover effective approaches to deep learning for computer vision, time series analysis, and forecasting

Purchase of the print or Kindle book includes a free PDF eBook

Book Description

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.

What you will learn

Discover different ways to transform data into valuable insights

Explore the different types of regression techniques

Grasp the basics of classification through Naive Bayes and decision trees

Use clustering to group data based on similarity measures

Perform data fitting, pattern recognition, and cluster analysis

Implement feature selection and extraction for dimensionality reduction

Harness MATLAB tools for deep learning exploration

Who this book is for

This book is for ML engineers, data scientists, DL engineers, and CV/NLP engineers who want to use MATLAB for machine learning and deep learning. A fundamental understanding of programming concepts is necessary to get started.

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