Machine Learning - Theory to Applications

The aim of this book is to teach core concepts of machine learning while focuses on modern applications. It is meant for anyone who wants to master machine learning by providing technical and practical insights.

List of contents

1. Introduction 2. Linear Algebra 3. Machine Learning 4. Some Practical Notes 5. Deep Learning 6. Generative Adversarial Networks 7. Implementation

About the author

Seyedeh Leili Mirtaheri is an assistant professor in the Electrical and Computer Engineering Department at Kharazmi University. She holds PhD degrees in computer engineering and also in operations research. She has authored several journal articles and conference proceedings and has also been an author/editor of several books. She has been a guest editor of the Journal of Supercomputing and also the reviewer of many credible journals.
Reza Shahbazian is an assistant professor of Standard Research Institute (Iran) and researcher at Unical. He holds PhD degrees in telecommunications and computer science. He has served as a postdoc researcher on applications of machine learning in telecommunication networks. He has authored several articles in journals and conference proceedings, book chapters and also authored or edited five books.

Summary

The aim of this book is to teach core concepts of machine learning while focuses on modern applications. It is meant for anyone who wants to master machine learning by providing technical and practical insights.

Product details

• Authors: Seyedeh Leili Mirtaheri, Seyedeh Leili (Electrical and Computer Mirtaheri, Reza Shahbazian
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Paperback / Softback
• Released: 30.09.2022
• EAN: 9780367634568
• ISBN: 978-0-367-63456-8
• No. of pages: 202
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Social sciences, law, business > Business > Miscellaneous; SCIENCE / Life Sciences / General, Artificial Intelligence, BUSINESS & ECONOMICS / Statistics, COMPUTERS / Machine Theory, MATHEMATICS / Arithmetic, environmental science, engineering & technology, algorithms and data structures, Probability & statistics, Algorithms & data structures, Information technology: general issues, Automatic control engineering, Probability and statistics, Environmental science, engineering and technology, Information technology: general topics