**Michael Paluszek, Stephanie Thomas ...**

326 pages -

**Publisher:**Apress; 1st edition (December, 2016) ...

**Language:**English -

**ISBN-10:**1484222490 -

**ISBN-13:**978-1484222492 ...

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.

**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.