MATLAB Machine Learning Recipes: A Problem-Solution Approach provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem, and all code is executable. 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. The primary audiences for this book are engineers, data scientists, and students.
In addition to MATLAB examples throughout the book, the book is also accompanied by a toolbox created by the authors in MATLAB.
- 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