MATLAB for Machine Learning (eBook)
374 Seiten
Packt Publishing (Verlag)
978-1-83508-953-8 (ISBN)
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.
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 applicationsKey FeaturesWork with the MATLAB Machine Learning Toolbox to implement a variety of machine learning algorithmsEvaluate, deploy, and operationalize your custom models, incorporating bias detection and pipeline monitoringUncover effective approaches to deep learning for computer vision, time series analysis, and forecastingPurchase of the print or Kindle book includes a free PDF eBookBook 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 learnDiscover different ways to transform data into valuable insightsExplore the different types of regression techniquesGrasp the basics of classification through Naive Bayes and decision treesUse clustering to group data based on similarity measuresPerform data fitting, pattern recognition, and cluster analysisImplement feature selection and extraction for dimensionality reductionHarness MATLAB tools for deep learning explorationWho 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.]]>
| Erscheint lt. Verlag | 30.1.2024 |
|---|---|
| Sprache | englisch |
| Themenwelt | Informatik ► Software Entwicklung ► User Interfaces (HCI) |
| Mathematik / Informatik ► Informatik ► Theorie / Studium | |
| Technik ► Elektrotechnik / Energietechnik | |
| ISBN-10 | 1-83508-953-4 / 1835089534 |
| ISBN-13 | 978-1-83508-953-8 / 9781835089538 |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
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