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Can I read Machine Learning: Discriminative and Generative (The Springer International Series in Engineering and Computer Science, 755) on EtoBox?
Machine Learning: Discriminative and Generative (The Springer International Series in Engineering and Computer Science, 755) by Tony Jebara is a nonfiction available to read on EtoBox.
What is Machine Learning: Discriminative and Generative (The Springer International Series in Engineering and Computer Science, 755) about?
Machine Learning: Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative support-vector machines. However, unlike previous books that only discuss these rather different approaches in isolation, it bridges the two schools of thought together within a common framework, elegantly connecting their various theories and making one common big-picture. Also, this bridge brings forth new hybrid discriminative-generative tools that combine the strengths of both camps. This book serves multiple purposes as well. The framework acts as a scientific breakthrough, fusing the areas of generative and discriminative learning and will be of interest to many researchers. However, as a conceptual breakthrough, this common framework unifies many previously unrelated tools and techniques and makes them understandable to a larger portion of the public. This gives the more practical-minded engineer, student and the industrial public an easy-access and more sensible road map into the world of machine learning. Machine Learning: Discriminative and Generative is designed for an audience composed of researche
Who reads Machine Learning: Discriminative and Generative (The Springer International Series in Engineering and Computer Science, 755)?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Tony Jebara
- Publisher
- Springer US : Imprint: Springer
- Published
- 2012
- Language
- EN
- ISBN
- 9781461347569
- Category
- nonfiction
- Subjects
- Mathematics, Engineering, Technology
- Updated
- 2026-03-24
Other editions & translations
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