MATLAB for Machine Learning - Second Edition: Unlock the power of deep learning for swift and enhanced results

Обкладинка - м"яка

Рік видання - 2024

Кількість сторінок - 374

Папір - білий, офсет

Master MATLAB tools for creating machine learning applications through effective code writing, guided by practical examples showcasing the versatility of machine learning in real-world applications

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

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.

Table of Contents

Exploring MATLAB for Machine Learning

Working with Data in MATLAB

Prediction Using Classification and Regression

Clustering Analysis and Dimensionality Reduction

Introducing Artificial Neural Networks Modeling

Deep Learning and Convolutional Neural Networks

Natural Language Processing Using MATLAB

MATLAB for Image Processing and Computer Vision

Time Series Analysis and Forecasting with MATLAB

MATLAB Tools for Recommender Systems

Anomaly Detection in MATLAB

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