Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book
provides a series of examples of technologies critical to machine learning. Each example solves
a real-world problem. All code in MATLAB Machine Learning Recipes: A Problem-Solution Approach
is executable. The toolbox that the code uses provides a complete set of functions needed to
implement all aspects of machine learning. Authors Michael Paluszek and Stephanie Thomas show
how all of these technologies allow the reader to build sophisticated applications to solve
problems with pattern recognition autonomous driving expert systems and much more. What
you'll learn: How to write code for machine learning adaptive control and estimation using
MATLAB How these three areas complement each other How these three areas are needed for robust
machine learning applications How to use MATLAB graphics and visualization tools for machine
learning How to code real world examples in MATLAB for major applications of machine learning
in big data Who is this book for: The primary audiences are engineers data scientists and
students wanting a comprehensive and code cookbook rich in examples on machine learning using
MATLAB.
