1.

Record Nr.

UNINA9910338008103321

Autore

Paluszek Michael

Titolo

MATLAB Machine Learning Recipes : A Problem-Solution Approach / / by Michael Paluszek, Stephanie Thomas

Pubbl/distr/stampa

Berkeley, CA : , : Apress : , : Imprint : Apress, , 2019

ISBN

9781523150373

1523150378

9781484239162

1484239164

Edizione

[2nd ed. 2019.]

Descrizione fisica

1 online resource (358 pages)

Disciplina

006.3

Soggetti

Artificial intelligence

Big data

Artificial Intelligence

Big Data

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

1 Overview -- 2 Data Representation -- 3 MATLAB Graphics -- 4 Kalman Filters -- 5 Adaptive Control -- 6 Fuzzy Logic -- 7 Data Classification with Decision Trees -- 8 Simple Neural Nets -- 9 Classification with Neural Nets -- 10 Neural Nets with Deep Learning -- 11 Neural Aircraft Control -- 12 Multiple Hypothesis Testing -- 13 Autonomous Driving with MHT -- 14 Case-Based Expert Systems -- Appendix A: A Brief History of Autonomous Learning -- Appendix B: Software for Machine Learning.

Sommario/riassunto

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. You will: Learn to write code for machine learning, adaptive control and estimation using MATLAB See how these three areas complement each other Understand why these three areas are needed for robust machine learning applications Use MATLAB graphics and visualization tools for machine learning Code real world examples in MATLAB for major applications of machine learning in big data .