Emanuel kitzelmann (8 Ergebnisse)

paperback. Zustand: Very Good. Most items will be dispatched the same or the next working day. A copy that has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Paperback. Zustand: Brand New. spiral-bound edition. 195 pages. 9.00x6.00x0.50 inches. In Stock.

Zustand: New. In English.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Inductive programming is concerned with the automated construction of decl- ative often functional recursiveprogramsfromincompletespeci cationssuch as input/output examples. The inferred program must be correct with respect to the provided examples in a generalizing sense: it should be neither equivalent to it, nor inconsistent. Inductive programming algorithms are guided explicitly or implicitly by a language bias (the class of programs that can be induced) and a search bias (determining which generalized program is constructed rst). Induction strategiesare either generate-and-testor example-driven.In genera- and-test approaches, hypotheses about candidate programs are generated in- pendently from the given speci cations. Program candidates are tested against the given speci cation and one or more of the best evaluated candidates are - veloped further. In analytical approaches, candidate programs are constructed in an example-driven way. While generate-and-test approaches can in prin- ple construct any kind of program, analytical approaches have a more limited scope. On the other hand, e ciency of induction is much higher in analytical approaches. Inductive programming is still mainly a topic of basic research, exploring how the intellectual ability of humans to infer generalized recursive procedures from incomplete evidence can be captured in the form of synthesis methods. Intended applications are mainly in the domain of programming assistance either to relieve professional programmers from routine tasks or to enable n- programmers to some limited form of end-user programming. Furthermore, in future,inductiveprogrammingtechniquesmightbe appliedtofurtherareassuch as support inference of lemmata in theorem proving or learning grammar rules.…

Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Inductive programming is concerned with the automated construction of decl- ative¿often functional ¿recursiveprogramsfromincompletespeci?cationssuch as input/output examples. The inferred program must be correct with respect to the provided examples in a generalizing sense: it should be neither equivalent to it, nor inconsistent. Inductive programming algorithms are guided explicitly or implicitly by a language bias (the class of programs that can be induced) and a search bias (determining which generalized program is constructed ?rst). Induction strategiesare either generate-and-testor example-driven.In genera- and-test approaches, hypotheses about candidate programs are generated in- pendently from the given speci?cations. Program candidates are tested against the given speci?cation and one or more of the best evaluated candidates are - veloped further. In analytical approaches, candidate programs are constructed in an example-driven way. While generate-and-test approaches can ¿ in prin- ple ¿ construct any kind of program, analytical approaches have a more limited scope. On the other hand, e?ciency of induction is much higher in analytical approaches. Inductive programming is still mainly a topic of basic research, exploring how the intellectual ability of humans to infer generalized recursive procedures from incomplete evidence can be captured in the form of synthesis methods. Intended applications are mainly in the domain of programming assistance ¿ either to relieve professional programmers from routine tasks or to enable n- programmers to some limited form of end-user programming. Furthermore, in future,inductiveprogrammingtechniquesmightbe appliedtofurtherareassuch as support inference of lemmata in theorem proving or learning grammar rules.…

Zustand: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Das Buch Künstliche Intelligenz für Lehrkräfte führt die zentralen Ansätze und Gebiete der KI fundiert und insbesondere für Informatiklehrkräfte aufbereitet ein. Es bietet aber auch Lehrkräften mit anderem Hintergrund die Möglichkeit, sich mit den fachlichen Grundlagen von KI auseinanderzusetzen. Behandelte Themen sind insbesondere Problemlösen und Suche, Grundlagen des Maschinellen Lernens, Wissensrepräsentation und Schließen, Künstliche neuronale Netze, Tiefes Lernen, Generative KI und Robotik. In jedem Kapitel wird eine methodische Einführung gegeben, relevante Anwendungsbereiche aufgezeigt und Vorschläge für die konkrete Umsetzung im Unterricht gegeben. Zudem werden interdisziplinäre Bezüge hergestellt und Fragen der Ethik und gesellschaftliche Bezüge diskutiert.Die Herausgebenden und Autor:innen des Buches sind Lehrkräfte an Hochschulen aus den BereichenKünstliche Intelligenz und Informatikdidaktik. Durch die interdisziplinäre Kooperation bietet das Buch sowohl einen fachlich fundierten Einstieg in das Thema KI alsauch einen geeigneten didaktischen Zugang.…

Taschenbuch. Zustand: Neu. Künstliche Intelligenz für Lehrkräfte | Eine fachliche Einführung mit didaktischen Hinweisen | Ulrich Furbach (u. a.) | Taschenbuch | ars digitalis | xii | Deutsch | 2024 | Springer Vieweg | EAN 9783658442477 | Verantwortliche Person für die EU: Springer Vieweg in Springer Science + Business Media, Abraham-Lincoln-Str. 46, 65189 Wiesbaden, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…