Apress | MATLAB Machine Learning Recipes: A Problem-Solution Approach, 2nd Edition (2019 EN)

Author: Michael Paluszek, Stephanie Thomas
Full Title: MATLAB Machine Learning Recipes: A Problem-Solution Approach, 2nd Edition
Publisher: Apress; 2nd ed. edition (February 1, 2019)
Year: 2019
ISBN-13: 9781484239162 (978-1-4842-3916-2), 9781484239155 (978-1-4842-3915-5)
ISBN-10: 1484239164, 1484239156
Pages: 347
Language: English
Genre: Educational: Artificial Intelligence
File type: PDF (True), Code Files
Quality: 10/10
Price: 26.74 €


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.


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

Features:
✓ Utilizes real world examples in MATLAB for major applications of machine learning in big data
✓ Comes with complete working MATLAB source code
✓ Shows how to use MATLAB graphics and visualization tools for machine learning

Who This Book Is For:
The primary audiences are engineers, data scientists and students wanting a comprehensive and code cookbook rich in examples on machine learning using MATLAB.

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