MATLAB Machine Learning

✍ Scribed by Michael Paluszek, Stephanie Thomas (auth.)

• Publisher: Apress
• Year: 2017
• Tongue: English
• Leaves: 335
• Edition: 1
• Category: Library

✦ Synopsis

This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It provides descriptions of all major areas in machine learning.

The book reviews commercially available packages for machine learning and shows how they fit into the field. The book then shows how MATLAB can be used to solve machine learning problems and how MATLAB graphics can enhance the programmer’s understanding of the results and help users of their software grasp the results.
Machine Learning can be very mathematical. The mathematics for each area is introduced in a clear and concise form so that even casual readers can understand the math. Readers from all areas of engineering will see connections to what they know and will learn new technology.
The book then provides complete solutions in MATLAB for several important problems in machine learning including face identification, autonomous driving, and data classification. Full source code is provided for all of the examples and applications in the book.

What you'll learn:

• An overview of the field of machine learning
  
• Commercial and open source packages in MATLAB
  
• How to use MATLAB for programming and building machine learning applications
  
• MATLAB graphics for machine learning
  
• Practical real world examples in MATLAB for major applications of machine learning in big data
  

Who is this book for:
The primary audiences are engineers and engineering students wanting a comprehensive and practical introduction to machine learning.

✦ Table of Contents

Front Matter....Pages I-XIX
Front Matter....Pages 1-1
An Overview of Machine Learning....Pages 3-15
The History of Autonomous Learning....Pages 17-23
Software for Machine Learning....Pages 25-31
Front Matter....Pages 33-33
Representation of Data for Machine Learning in MATLAB....Pages 35-48
MATLAB Graphics....Pages 49-84
Machine Learning Examples in MATLAB....Pages 85-88
Face Recognition with Deep Learning....Pages 89-112
Data Classification....Pages 113-141
Classification of Numbers Using Neural Networks....Pages 143-167
Kalman Filters....Pages 169-205
Adaptive Control....Pages 207-268
Autonomous Driving....Pages 269-322
Back Matter....Pages 323-326

✦ Subjects

Computing Methodologies;Programming Languages, Compilers, Interpreters;Programming Techniques