MATLAB for Machine Learning - Second Edition

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Free Download MATLAB for Machine Learning - Second Edition: Unlock the power of deep learning for swift and enhanced results by Giuseppe Ciaburro
English | January 30, 2024 | ISBN: 1835087698 | 374 pages | EPUB | 8.61 Mb
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 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 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 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 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 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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Learning MATLAB
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hour 13M | 185 MB
Genre: eLearning | Language: English​

MATLAB is one of the most popular programming languages today for engineers and scientists, and with good reason-it allows analysts to work efficiently with large amounts of data. Instructor Steven Moser shows you how to harness the MATLAB tools and create programs to model your own data and hypotheses. First, learn how to create basic variables and cell arrays, and work with the core MATLAB syntax, which is significantly different than other programming languages. Then discover how to create scripts and functions, work with matrices, debug your program, and import data. To illustrate your findings, Steven shows how to create 2D and 3D plots, add annotations, and incorporate images. The final chapter covers Simulink, the MATLAB block diagram tool.

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