MATLAB for Machine Learning

Meer over het boek

Extract patterns and knowledge from your data easily using MATLAB. This guide introduces machine learning concepts, covering regression, clustering, classification, predictive analytics, and artificial neural networks. It is designed for data analysts, scientists, students, or anyone eager to delve into machine learning and develop efficient data processing applications. A background in mathematics and statistics will enhance comprehension. You will learn the fundamentals of machine learning, data transformation techniques, and how to use SAS XPORT for data handling. The book explores various regression techniques, including simple and multiple linear regression, ordinary least squares estimation, and correlations. It also covers classification methods, implementing algorithms like Naive Bayes and Decision Trees in MATLAB. Clustering techniques, such as hierarchical clustering, are discussed for data grouping based on similarity measures. The MATLAB Neural Network Toolbox is introduced for data fitting, pattern recognition, and clustering analysis. You'll learn about feature selection and extraction for dimensionality reduction, improving performance. The book provides a solid foundation in machine learning with MATLAB, guiding you through system setup, data cleansing, mining, and analysis. Real-world examples and use cases support your understanding, enabling you to apply concepts effectively in your work. By the end, you'l