MATLAB for Machine Learning - Second Edition
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MATLAB for Machine Learning - Second Edition
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Overview of this book
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.
Table of Contents (17 chapters)
Preface
Chapter 1: Exploring MATLAB for Machine Learning
Chapter 2: Working with Data in MATLAB
Part 2: Understanding Machine Learning Algorithms in MATLAB
Chapter 3: Prediction Using Classification and Regression
Chapter 4: Clustering Analysis and Dimensionality Reduction
Chapter 5: Introducing Artificial Neural Network Modeling
Chapter 6: Deep Learning and Convolutional Neural Networks
Part 3: Machine Learning in Practice
Chapter 7: Natural Language Processing Using MATLAB
Chapter 8: MATLAB for Image Processing and Computer Vision
Chapter 9: Time Series Analysis and Forecasting with MATLAB
Chapter 10: MATLAB Tools for Recommender Systems
Chapter 11: Anomaly Detection in MATLAB
Index
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