Machine Learning
from the classics to deep networks, transformers, and diffusion models
$308.38
- Paperback
1200 pages
- Release Date
20 April 2025
Summary
Machine Learning: From Classics to Cutting-Edge
Machine Learning: From the Classics to Deep Networks, Transformers and Diffusion Models, Third Edition starts with the basics, including least squares regression and maximum likelihood methods, Bayesian decision theory, logistic regression, and decision trees. It then progresses to more recent techniques, covering sparse modelling methods, learning in reproducing kernel Hilbert spaces and support vector machines.
Bayesian learn…
Book Details
| ISBN-13: | 9780443292385 |
|---|---|
| ISBN-10: | 0443292388 |
| Author: | Sergios Theodoridis |
| Publisher: | Elsevier Science Publishing Co Inc |
| Imprint: | Academic Press Inc |
| Format: | Paperback |
| Number of Pages: | 1200 |
| Edition: | 3rd |
| Release Date: | 20 April 2025 |
| Weight: | 2.00kg |
| Dimensions: | 235mm x 191mm |
About The Author
Sergios Theodoridis
Sergios Theodoridis is professor emeritus of machine learning and data processing with the National and Kapodistrian University of Athens, Athens, Greece. He has also served as distinguished professor with the Aalborg University Denmark and as professor with the Chinese University of Hong Kong, Shenzhen, China. In 2023, he received an honorary doctorate degree (D.Sc) from the University of Edinburgh, U.K. He has also received a number of prestigious awards, including the 2014 IEEE Signal Processing Magazine Best Paper Award, the 2009 IEEE Computational Intelligence Society Transactions on Neural Networks Outstanding Paper Award, the 2017 European Association for Signal Processing (EURASIP) Athanasios Papoulis Award, the 2014 IEEE Signal Processing Society Carl Friedrich Gauss Education Award, and the 2014 EURASIP Meritorious Service Award. He has served as president of EURASIP and vice president for the IEEE Signal Processing Society. He is a Fellow of EURASIP and a Life Fellow of IEEE. He is the coauthor of the book Pattern Recognition, 4th edition, Academic Press, 2009 and of the book Introduction to Pattern Recognition: A MATLAB Approach, Academic Press, 2010.
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