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 Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDiscover 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 forThis 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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Table of ContentsExploring MATLAB for Machine LearningWorking with Data in MATLABPrediction Using Classification and RegressionClustering Analysis and Dimensionality ReductionIntroducing Artificial Neural Networks ModelingDeep Learning and Convolutional Neural NetworksNatural Language Processing Using MATLABMATLAB for Image Processing and Computer VisionTime Series Analysis and Forecasting with MATLABMATLAB Tools for Recommender SystemsAnomaly Detection in MATLAB
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Produktdetaljer

ISBN
9781835087695
Publisert
2024-01-30
Utgave
2. utgave
Utgiver
Vendor
Packt Publishing Limited
Høyde
235 mm
Bredde
191 mm
AldersnivĂĽ
01, G, 01
SprĂĽk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
374

Forfatter

Om bidragsyterne

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - UniversitĂ  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).