MATLAB for Machine Learning
Practical examples of regression, clustering and neural networks
1st Edition
Published on 3. June 2024
382 pages
978-1-78839-939-5 (ISBN)
Description
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Giuseppe Ciaburro
MATLAB for Machine Learning
Unlock the power of deep learning for swift and enhanced results
E-Book
09/2024
2nd Edition
Packt Publishing
€31.99
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Persons
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).
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).
Content
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
- 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
