A coherent introduction to core concepts and deep learning techniques that are critical to academic research and real-world applications.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Hui Jiang is Professor of Electrical Engineering and Computer Science at York University, where he has been since 2002. His main research interests include machine learning, particularly deep learning, and its applications to speech and audio processing, natural language processing, and computer vision. Over the past 30 years, he has worked on a wide range of research problems from these areas and published hundreds of technical articles and papers in the mainstream journals and top-tier conferences. His works have won the prestigious IEEE Best Paper Award and the ACL Outstanding Paper honor.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
EUR 17,16 per la spedizione da U.S.A. a Italia
Destinazione, tempi e costiEUR 17,16 per la spedizione da U.S.A. a Italia
Destinazione, tempi e costiDa: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 42948896
Quantità: 1 disponibili
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New. Codice articolo 42948896-n
Quantità: 1 disponibili
Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In. Codice articolo ria9781108837040_new
Quantità: Più di 20 disponibili
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: As New. Unread book in perfect condition. Codice articolo 42948896
Quantità: 1 disponibili
Da: California Books, Miami, FL, U.S.A.
Condizione: New. Codice articolo I-9781108837040
Quantità: Più di 20 disponibili
Da: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This lucid and coherent introduction to supervised machine learning presents core concepts in a concise, logical and easy-to-follow way for readers with some mathematical preparation but no prior exposure to machine learning. Coverage includes widely used t. Codice articolo 497289512
Quantità: Più di 20 disponibili
Da: Revaluation Books, Exeter, Regno Unito
Hardcover. Condizione: Brand New. 400 pages. 10.20x8.15x1.06 inches. In Stock. This item is printed on demand. Codice articolo __1108837042
Quantità: 1 disponibili
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: New. Codice articolo 42948896-n
Quantità: 1 disponibili
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
Hardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 1061. Codice articolo C9781108837040
Quantità: Più di 20 disponibili
Da: CitiRetail, Stevenage, Regno Unito
Hardcover. Condizione: new. Hardcover. This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely from scratch based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts. This lucid and coherent introduction to supervised machine learning presents core concepts in a concise, logical and easy-to-follow way for readers with some mathematical preparation but no prior exposure to machine learning. Coverage includes widely used traditional methods plus recently popular deep learning methods. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9781108837040
Quantità: 1 disponibili