Articoli correlati a Kernel Methods and Machine Learning
Sinossi
Covering the fundamentals of kernel-based learning theory, this is an essential resource for graduate students and professionals in computer science.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sull?autore
S. Y. Kung is a Professor in the Department of Electrical Engineering at Princeton University. His research areas include VLSI array/parallel processors, system modeling and identification, wireless communication, statistical signal processing, multimedia processing, sensor networks, bioinformatics, data mining and machine learning.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Compra usato
Condizioni: come nuovoPage block firm and clean, binding...
Visualizza questo articolo
EUR 56,98
EUR 42,57 per la spedizione da U.S.A. a Italia
Destinazione, tempi e costiCompra nuovo
Visualizza questo articolo
EUR 102,24
EUR 17,02 per la spedizione da U.S.A. a Italia
Destinazione, tempi e costiRisultati della ricerca per Kernel Methods and Machine Learning
Foto dell'editore
Kernel Methods and Machine Learning
Editore:
Cambridge University Press, 2014
ISBN 10: 110702496X
ISBN 13: 9781107024960
Antico o usato
Rilegato
Da: thebookforest.com, San Rafael, CA, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: LikeNew. Page block firm and clean, binding unblemished, boards straight, no markings of any kind. Fine, like new condition. Well packaged and promptly shipped from California. Partnered with Friends of the Library since 2010. Codice articolo 1LAGBP001YHO
Quantità: 1 disponibili
Immagini fornite dal venditore
Kernel Methods and Machine Learning
Editore:
Cambridge University Press, 2014
ISBN 10: 110702496X
ISBN 13: 9781107024960
Antico o usato
Rilegato
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: As New. Unread book in perfect condition. Codice articolo 19977914
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Kernel Methods and Machine Learning
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo 19977914-n
Quantità: Più di 20 disponibili
Foto dell'editore
Kernel Methods and Machine Learning
Da: Ria Christie Collections, Uxbridge, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. In. Codice articolo ria9781107024960_new
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Kernel Methods and Machine Learning
Print on DemandDa: moluna, Greven, Germania
Valutazione del venditore 5 su 5 stelle
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Containing numerous algorithms and major theorems, this step-by-step guide covers the fundamentals of kernel-based learning theory. Including over two hundred problems and real-world examples, it is an essential resource for graduate students and profession. Codice articolo 5994623
Quantità: Più di 20 disponibili
Foto dell'editore
Kernel Methods and Machine Learning
Print on DemandDa: Revaluation Books, Exeter, Regno Unito
Valutazione del venditore 5 su 5 stelle
Hardcover. Condizione: Brand New. 591 pages. 10.00x6.00x1.00 inches. In Stock. This item is printed on demand. Codice articolo __110702496X
Quantità: 1 disponibili
Immagini fornite dal venditore
Kernel Methods and Machine Learning
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo 19977914-n
Quantità: Più di 20 disponibili
Foto dell'editore
Kernel Methods and Machine Learning (Hardcover)
Editore:
Cambridge University Press, Cambridge, 2014
ISBN 10: 110702496X
ISBN 13: 9781107024960
Nuovo
Rilegato
Da: AussieBookSeller, Truganina, VIC, Australia
Valutazione del venditore 5 su 5 stelle
Hardcover. Condizione: new. Hardcover. Offering a fundamental basis in kernel-based learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernel-based supervised and unsupervised learning models. The first of the theorems establishes a condition, arguably necessary and sufficient, for the kernelization of learning models. In addition, several other theorems are devoted to proving mathematical equivalence between seemingly unrelated models. With over 25 closed-form and iterative algorithms, the book provides a step-by-step guide to algorithmic procedures and analysing which factors to consider in tackling a given problem, enabling readers to improve specifically designed learning algorithms, build models for new applications and develop efficient techniques suitable for green machine learning technologies. Numerous real-world examples and over 200 problems, several of which are Matlab-based simulation exercises, make this an essential resource for graduate students and professionals in computer science, electrical and biomedical engineering. Solutions to problems are provided online for instructors. Containing numerous algorithms and major theorems, this step-by-step guide covers the fundamentals of kernel-based learning theory. Including over two hundred problems and real-world examples, it is an essential resource for graduate students and professionals in computer science, electrical and biomedical engineering. Solutions to problems are provided online for instructors. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9781107024960
Quantità: 1 disponibili
Foto dell'editore
Kernel Methods and Machine Learning (Hardcover)
Editore:
Cambridge University Press, Cambridge, 2014
ISBN 10: 110702496X
ISBN 13: 9781107024960
Nuovo
Rilegato
Da: CitiRetail, Stevenage, Regno Unito
Valutazione del venditore 5 su 5 stelle
Hardcover. Condizione: new. Hardcover. Offering a fundamental basis in kernel-based learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernel-based supervised and unsupervised learning models. The first of the theorems establishes a condition, arguably necessary and sufficient, for the kernelization of learning models. In addition, several other theorems are devoted to proving mathematical equivalence between seemingly unrelated models. With over 25 closed-form and iterative algorithms, the book provides a step-by-step guide to algorithmic procedures and analysing which factors to consider in tackling a given problem, enabling readers to improve specifically designed learning algorithms, build models for new applications and develop efficient techniques suitable for green machine learning technologies. Numerous real-world examples and over 200 problems, several of which are Matlab-based simulation exercises, make this an essential resource for graduate students and professionals in computer science, electrical and biomedical engineering. Solutions to problems are provided online for instructors. Containing numerous algorithms and major theorems, this step-by-step guide covers the fundamentals of kernel-based learning theory. Including over two hundred problems and real-world examples, it is an essential resource for graduate students and professionals in computer science, electrical and biomedical engineering. Solutions to problems are provided online for instructors. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9781107024960
Quantità: 1 disponibili
Foto dell'editore
Kernel Methods and Machine Learning
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo ABLIING23Mar2317530264105
Quantità: Più di 20 disponibili