Ciaburro / Kolluru MATLAB for Machine Learning

Practical examples of regression, clustering and neural networks
1. Auflage 2017
ISBN: 978-1-78839-939-5
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 382 Seiten

No detailed description available for "MATLAB for Machine Learning".

Autoren/Hrsg.

Ciaburro, Giuseppe

Kolluru, Pavan Kumar

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Table of Contents - Getting Started with Matlab Machine Learning

- Importing and organizing data in Matlab

- From data to knowledge discovery

- Finding relationships between variables - Regression techniques

- Pattern recognition through classification algorithms

- Identifying groups of data by clustering methods

- Simulation of human thinking - Artificial neural networks

- Improves the performance of the machine learning model - Dimensionality reduction

- Machine learning in practice

Über Autor(innen)

Ciaburro Giuseppe:

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).