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Machine Learning for Engineers
Osvaldo Simeone
(Author)
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Cambridge University Press
· Hardcover
Machine Learning for Engineers - Simeone, Osvaldo
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Origin: Spain
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Tuesday, July 09 and
Tuesday, July 16.
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Synopsis "Machine Learning for Engineers"
This self-contained introduction to machine learning, designed from the start with engineers in mind, will equip students with everything they need to start applying machine learning principles and algorithms to real-world engineering problems. With a consistent emphasis on the connections between estimation, detection, information theory, and optimization, it includes: an accessible overview of the relationships between machine learning and signal processing, providing a solid foundation for further study; clear explanations of the differences between state-of-the-art techniques and more classical methods, equipping students with all the understanding they need to make informed technique choices; demonstration of the links between information-theoretical concepts and their practical engineering relevance; reproducible examples using Matlab, enabling hands-on student experimentation. Assuming only a basic understanding of probability and linear algebra, and accompanied by lecture slides and solutions for instructors, this is the ideal introduction to machine learning for engineering students of all disciplines.
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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.
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