9780792392774 - foundations of knowledge acquisition: cognitive models of complex learning (the springer international series in engineering and computer science, 194, band 194) (5 Ergebnisse)
- Hardcover
- Erstausgabe
Anbieter: Plurabelle Books Ltd, Cambridge, Vereinigtes KönigreichPlurabelle Books Ltd
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Zustand: Gebraucht - Gut
EUR 28,93
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Hardcover. Zustand: Very Good. Series: International Series in Engineering and Computer Science. x 339p hardback with laminated cover, very good copy from a Cambridge college library, library markings crossed out, a very good, unused copy Language: English.
- Hardcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
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Zustand: New. In.
- Hardcover
Anbieter: moluna, Greven, Deutschlandmoluna
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EUR 180,97
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Gebunden. Zustand: New. One of the most intriguing questions about the new computer technology that has appeared over the past few decades is whether we humans will ever be able to make computers learn. As is painfully obvious to even the most casual computer user, most current co.
- Hardcover
Anbieter: Kennys Bookstore, Olney, MD, USAKennys Bookstore
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EUR 253,89
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Zustand: New. Documents the progress of basic research in knowledge acquisition sponsored by the Office of Naval Research. This title includes summaries of work by cognitive scientists who do computational modeling of human learning. It also includes work in analogical reasoning; induction and discovery; explanation-based learni…ng; and, more. Editor(s): Chipman, Susan F.; Meyrowitz, Alan L. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 339 pages, biography. BIC Classification: UYQM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 20. Weight in Grams: 1490. . 1992. Hardback. . . . . Books ship from the US and Ireland.
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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EUR 223,29
EUR 63,36 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Buch. Zustand: Neu. Neuware - One of the most intriguing questions about the new computer technology that has appeared over the past few decades is whether we humans will ever be able to make computers learn. As is painfully obvious to even the most casual computer user, most current computers do not. Yet if we could devise lear…ning techniques that enable computers to routinely improve their performance through experience, the impact would be enormous. The result would be an explosion of new computer applications that would suddenly become economically feasible (e. g. , personalized computer assistants that automatically tune themselves to the needs of individual users), and a dramatic improvement in the quality of current computer applications (e. g. , imagine an airline scheduling program that improves its scheduling method based on analyzing past delays). And while the potential economic impact ofsuccessful learning methods is sufficient reason to invest in research into machine learning, there is a second significant reason: studying machine learning helps us understand our own human learning abilities and disabilities, leading to the possibility of improved methods in education. While many open questions remain aboutthe methods by which machines and humans might learn, significant progress has been made.
