Machine Learning
Discriminative and Generative
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Beschreibung
Machine Learning is a powerful new field with many important practical applications. Thanks to the information age and flood of data, it has taken many domains by storm including biology, text processing, internet data organization, computer vision, speech recognition, computer-human interfaces, robotics, and artificial intelligence. This easy-access book covers the main contemporary themes and tools in machine learning, ranging from Bayesian probabilistic models to discriminative support-vector machines. Unlike previous books, it bridges these two schools of thought together within a common framework, elegantly connecting their various theories and combining their strengths into one common big-picture.
Autor*in
Tony Jebara
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From the reviews:
"This book aims to unite two powerful approaches in machine learning: generative and discriminative. … Researchers from the generative or discriminative schools will find this book a nice bridge to the other paradigm." (C. Andy Tsao, Mathematical Reviews, Issue 2005 k)
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