Machine Learning / Deep Learning

Abstract

MATLAB is an exceptional platform for diving into the world of machine learning, offering a robust environment that integrates data analysis, visualization, and algorithm development seamlessly. In an introductory MATLAB machine learning tutorial, you'll be introduced to and familiarized with the MATLAB Machine Learning toolbox interface and its extensive documentation, which is designed to help both beginners and advanced users. You'll learn how to prepare data, a crucial step that involves cleaning and transforming raw data into a format suitable for analysis. This includes handling missing values, normalizing data, and feature extraction. Once your data is ready, we will explore machine learning techniques such as regression, which is used for predicting continuous outcomes, and classification, which is used for categorizing data into discrete classes. We will also delve into clustering methods, which group data based on similarities, and deep learning, which involves neural networks with multiple layers that can model complex patterns in data. Throughout the tutorial, you'll apply these techniques to datasets, gaining practical experience in training models, tuning hyperparameters, and evaluating model performance using metrics like accuracy, precision, and recall. By the end of the tutorial, you'll have a solid understanding of machine learning principles and hands-on experience with MATLAB's powerful tools, enabling you to tackle complex problems and develop sophisticated machine learning models.