MATLAB for Machine Learning: Unlock the power of deep learning for swift and enhanced results, Edition 2
About this ebook
- Work with the MATLAB Machine Learning Toolbox to implement a variety of machine learning algorithms
- Evaluate, deploy, and operationalize your custom models, incorporating bias detection and pipeline monitoring
- Uncover effective approaches to deep learning for computer vision, time series analysis, and forecasting
- Purchase of the print or Kindle book includes a free PDF eBook
- Discover different ways to transform data into valuable insights
- Explore the different types of regression techniques
- Grasp the basics of classification through Naive Bayes and decision trees
- Use clustering to group data based on similarity measures
- Perform data fitting, pattern recognition, and cluster analysis
- Implement feature selection and extraction for dimensionality reduction
- Harness MATLAB tools for deep learning exploration
This book is for ML engineers, data scientists, DL engineers, and CV/NLP engineers who want to use MATLAB for machine learning and deep learning. A fundamental understanding of programming concepts is necessary to get started.
About the author
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).
