MATLAB Machine Learning Recipes by Michael Paluszek

MATLAB Machine Learning Recipes by Michael Paluszek

View All Editions
Regular price
Checking stock...

MATLAB Machine Learning Recipes

MATLAB Machine Learning Recipes by Michael Paluszek

Harness the power of MATLAB to resolve a wide range of machine learning challenges. This new and updated third edition provides examples of technologies critical to machine learning. Each example solves a real-world problem, and all code provided is executable. You can easily look up a particular problem and follow the steps in the solution. This book has something for everyone interested in machine learning. It also has material that will allow those with an interest in other technology areas to see how machine learning and MATLAB can help them solve problems in their areas of expertise. The chapter on data representation and MATLAB graphics includes new data types and additional graphics. Chapters on fuzzy logic, simple neural nets, and autonomous driving have new examples added. And there is a new chapter on spacecraft attitude determination using neural nets. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow you to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more. What You Will Learn Write code for machine learning, adaptive control, and estimation using MATLAB Use MATLAB graphics and visualization tools for machine learning Become familiar with neural nets Build expert systems Understand adaptive control Gain knowledge of Kalman Filters Who This Book Is For Software engineers, control engineers, university faculty, undergraduate and graduate students, hobbyists.
SKU Unavailable
ISBN 13
Title MATLAB Machine Learning Recipes
Author Michael Paluszek
Condition Unavailable
Binding Type
Publisher
Year published
Cover note Book picture is for illustrative purposes only, actual binding, cover or edition may vary.

View All Editions

Filters

Loading editions...

⚠️

Unable to load editions. Please refresh the page to try again.