Book Image

MATLAB for Machine Learning - Second Edition

By : Giuseppe Ciaburro
Book Image

MATLAB for Machine Learning - Second Edition

By: Giuseppe Ciaburro

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)
Free Chapter
1
Part 1: Getting Started with Matlab
4
Part 2: Understanding Machine Learning Algorithms in MATLAB
9
Part 3: Machine Learning in Practice

Introducing Artificial Neural Network Modeling

Artificial neural networks (ANNs) include data structures and algorithms for learning and classifying data. Through neural network techniques, a program can learn through examples and create an internal structure of rules to classify different inputs. MATLAB provides algorithms, pre-trained models, and apps to create, train, visualize, and simulate ANNs. In this chapter, we will see how to use MATLAB to build an ANN-based model to predict values and classify data.

In this chapter, we’re going to cover the following main topics:

  • Getting started with ANNs
  • Training and testing an ANN model in MATLAB
  • Understanding data fitting with ANNs
  • Discovering pattern recognition using ANNs
  • Building a clustering application with an ANN
  • Exploring advanced optimization techniques