Meyrowitz alan (56 résultats)

paperback. Etat : Very Good. Paperback. NOT Ex-library. Very good condition. Slight edgewear and bumping. Clean pages and tight binding. Until further notice, USPS Priority Mail only reliable option for Hawaii. Proceeds benefit the Pima County Public Library system, which serves Tucson and southern Arizona.…

Etat : New.

Etat : New.

Etat : As New. Unread book in perfect condition.

Hardcover. Etat : As New.

Etat : New. In English.

Etat : New.

Etat : As New. Unread book in perfect condition.

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hardcover. Etat : Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority.

Hardcover. Etat : New. In shrink wrap. Looks like an interesting title.

Etat : Hervorragend. Zustand: Hervorragend | Seiten: 334 | Sprache: Englisch | Produktart: Bücher | 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 learning 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 of successful 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 about the methods by which machines and humans might learn, significant progress has been made.…

PAP. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

Etat : New. In English.

Etat : New. In English.

Etat : New. In English.

Etat : New. In English.

Etat : New.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

Etat : New.

Etat : New.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 learning 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 of successful 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 about the methods by which machines and humans might learn, significant progress has been made.…

Etat : 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 learning; 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. . . . .…

Etat : New. pp. 352.

Etat : New. pp. 356.

Etat : New. pp. 352.