Become well-versed with the tools available in MATLAB to create a machine learning-based application and write code effectively. Readers will explore several practical examples of Machine Learning applications using MATLAB.
Key Features
- Explore the MATLAB Machine learning toolbox to implement various Machine Learning algorithms.
- Evaluate, deploy, and operationalize your custom models with bias detection and pipeline monitoring.
- Discover how to approach Deep Learning for Computer Vision and Time Series Analysis and Forecasting.
Book Description
MATLAB is a comprehensive programming environment used by many researchers and math experts for machine learning. This book will help you learn the basic concepts in machine learning and deep learning using MATLAB and then refine your basic skills with advanced applications. You'll start by exploring the tools that the MATLAB environment offers for machine learning and see how to easily interact with the MATLAB workspace. We'll then move on to data cleansing, mining, and analyzing various types of data in machine learning, and you'll see how to visualize data values on a graph. Next, you'll learn about the different types of classification and regression techniques and how to apply them to your data using MATLAB functions. Further, you will understand the basic concepts of neural networks and perform data fitting, pattern recognition and clustering analysis. You will also explore feature selection and extraction techniques for dimensionality reduction for performance improvement. Finally, you'll learn how to leverage MATLAB tools for deep learning and managing convolutional neural networks. By the end of the book, you'll learn how to put it all together in real-world cases covering major machine learning algorithms, and you'll feel confident as you delve into machine learning with MATLAB.
What you will learn
- Discover different ways to transform data into valuable insights
- Explore the different types of regression techniques
- Learn the basics of classification using Naive Bayes and decision trees
- Learn how to use clustering to group data using similarity measures
- Perform data fitting, pattern recognition, and clustering analysis
- Implement feature selection and extraction for dimensionality reduction
- Explore MATLAB tools for deep learning
Who this book is for
This book is designated to ML engineers, Data Scientists, DL engineers, CV/NLP engineers who want to use MATLAB for Machine learning and Deep Learning. Readers should have a fundamental understanding of programming concepts.
