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Revolutionary Mathematics: Artificial Intelligence, Statistics and the Logic of Capitalism
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In den WarenkorbPaperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
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Revolutionary Mathematics: Artificial Intelligence, Statistics and the Logic of Capitalism
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Revolutionary Mathematics: Artificial Intelligence, Statistics and the Logic of Capitalism
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbPaperback. Zustand: Brand New. 208 pages. 8.00x5.50x0.50 inches. In Stock.
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Revolutionary Mathematics: Artificial Intelligence, Statistics and the Logic of Capitalism Paperback ? January 11, 2022
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The Statistics and Calculus with Python Workshop: A comprehensive introduction to mathematics in Python for artificial intelligence applications
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paperback. Zustand: Very Good.
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Artificial Intelligence and Statistics William A. Gale
Anbieter: Versandantiquariat Claudia Graf, Lüdenscheid, Deutschland
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*geb. Zustand: Gut. 434 Seiten, 743 g - gut u. sauber mit wenigen Spuren, unkenntlich gemachter Namensaufkleber (siehe meine Fotos) / sw. --- in good condition with only few signs of use or age Sprache: Englisch Gewicht in Gramm: 743.
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Artificial Intelligence and Statistics
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Gebundene Ausgabe. Zustand: Sehr gut. 434 Seiten ex Library Book aus einer wissenschaftlichen Bibliothek Sprache: Englisch Gewicht in Gramm: 969.
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Revolutionary Mathematics: Artificial Intelligence, Statistics and the Logic of Capitalism
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Revolutionary Mathematics: Artificial Intelligence, Statistics and the Logic of Capitalism
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Zustand: New. 2022. Paperback. . . . . . Books ship from the US and Ireland.
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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.
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Operations Research and Artificial Intelligence in Healthcare Management: SSHSM, Quà bec, Canada, June 2022, and Lyon, France, June 2023 (Springer Proceedings in Mathematics & Statistics, 506)
Buch 424 von 464: Springer Proceedings in Mathematics & StatisticsAnbieter: Books From California, Simi Valley, CA, USA
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hardcover. Zustand: Fine.
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Artificial Intelligence and Statistics
Sprache: Englisch
Verlag: Longman Higher Education 01.03.1986., 1986
ISBN 10: 0201115697 ISBN 13: 9780201115697
Anbieter: NEPO UG, Rüsselsheim am Main, Deutschland
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Zustand: Gut. 434 Seiten ex Library Book aus einer wissenschafltichen Bibliothek Altersfreigabe FSK ab 0 Jahre Sprache: Englisch Gewicht in Gramm: 969 23,9 x 15,5 x 3,3 cm, Gebundene Ausgabe.
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Artificial Intelligence and Statistics
Anbieter: NEPO UG, Rüsselsheim am Main, Deutschland
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Gebundene Ausgabe. Zustand: Gut. 434 Seiten Aus einer gewerblichen Bibliothek from a commercial library Sprache: Englisch Gewicht in Gramm: 969.
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The Statistics and Calculus with Python Workshop: A comprehensive introduction to mathematics in Python for artificial intelligence applications
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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In den WarenkorbZustand: New. In.
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Zustand: New. Traces the revolution in statistics that gave rise to artificial intelligence and predictive algorithms refiguring contemporary capitalism.Über den AutorJustin Joque researches philosophy, technology and media and is the visuali.
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Machine Learning Mathematics: Study Deep Learning Through Data Science. How to Build Artificial Intelligence Through Concepts of Statistics, Algorit
Buch 3 von 3: Machine LearningAnbieter: ThriftBooks-Atlanta, AUSTELL, GA, USA
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Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
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Revolutionary Mathematics : Artificial Intelligence, Statistics and the Logic of Capitalism
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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Taschenbuch. Zustand: Neu. Neuware - Traces the revolution in statistics that gave rise to artificial intelligence and predictive algorithms refiguring contemporary capitalism.
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Taschenbuch. Zustand: Neu. Revolutionary Mathematics | Artificial Intelligence, Statistics and the Logic of Capitalism | Justin Joque | Taschenbuch | Kartoniert / Broschiert | Englisch | 2022 | Verso Books | EAN 9781788734004 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Statistics with Julia: Fundamentals for Data Science, Machine Learning and Artificial Intelligence (Springer Series in the Data Sciences)
Buch 8 von 11: Springer Series in the Data SciencesAnbieter: Studibuch, Stuttgart, Deutschland
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hardcover. Zustand: Sehr gut. 539 Seiten; 9783030709006.2 Gewicht in Gramm: 3.
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Selecting Models from Data: Artificial Intelligence and Statistics IV (Lecture Notes in Statistics, 89)
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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EUR 114,40
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In den WarenkorbZustand: New. In.
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Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
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Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
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Plunkett's Artificial Intelligence (AI) & Machine Learning Industry Almanac 2021: Artificial Intelligence (AI) & Machine Learning Industry Market Research, Statistics, Trends and Leading Companies
Anbieter: Friends of the Multnomah County Library, Portland, OR, USA
Verkäuferbewertung 5 von 5 Sternen
Soft cover. Zustand: Good. Ex-library copy. Clean pages, sound binding.
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Artificial Intelligence Frontiers in Statistics
Anbieter: Phatpocket Limited, Waltham Abbey, HERTS, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 138,15
EUR 12,29 Versand
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In den WarenkorbZustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
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Selecting Models from Data: Artificial Intelligence and Statistics IV
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 153,15
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In den WarenkorbPaperback. Zustand: Brand New. 497 pages. 9.25x6.00x1.00 inches. In Stock.
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Zustand: Gut. Zustand: Gut | Seiten: 468 | Sprache: Englisch | Produktart: Bücher | Ten years ago Bill Gale of AT&T Bell Laboratories was primary organizer of the first Workshop on Artificial Intelligence and Statistics. In the early days of the Workshop series it seemed clear that researchers in AI and statistics had common interests, though with different emphases, goals, and vocabularies. In learning and model selection, for example, a historical goal of AI to build autonomous agents probably contributed to a focus on parameter-free learning systems, which relied little on an external analyst's assumptions about the data. This seemed at odds with statistical strategy, which stemmed from a view that model selection methods were tools to augment, not replace, the abilities of a human analyst. Thus, statisticians have traditionally spent considerably more time exploiting prior information of the environment to model data and exploratory data analysis methods tailored to their assumptions. In statistics, special emphasis is placed on model checking, making extensive use of residual analysis, because all models are 'wrong', but some are better than others. It is increasingly recognized that AI researchers and/or AI programs can exploit the same kind of statistical strategies to good effect. Often AI researchers and statisticians emphasized different aspects of what in retrospect we might now regard as the same overriding tasks.
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 468 | Sprache: Englisch | Produktart: Bücher | Ten years ago Bill Gale of AT&T Bell Laboratories was primary organizer of the first Workshop on Artificial Intelligence and Statistics. In the early days of the Workshop series it seemed clear that researchers in AI and statistics had common interests, though with different emphases, goals, and vocabularies. In learning and model selection, for example, a historical goal of AI to build autonomous agents probably contributed to a focus on parameter-free learning systems, which relied little on an external analyst's assumptions about the data. This seemed at odds with statistical strategy, which stemmed from a view that model selection methods were tools to augment, not replace, the abilities of a human analyst. Thus, statisticians have traditionally spent considerably more time exploiting prior information of the environment to model data and exploratory data analysis methods tailored to their assumptions. In statistics, special emphasis is placed on model checking, making extensive use of residual analysis, because all models are 'wrong', but some are better than others. It is increasingly recognized that AI researchers and/or AI programs can exploit the same kind of statistical strategies to good effect. Often AI researchers and statisticians emphasized different aspects of what in retrospect we might now regard as the same overriding tasks.
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Zustand: Gut. Zustand: Gut | Seiten: 504 | Sprache: Englisch | Produktart: Bücher | This volume is a selection of papers presented at the Fourth International Workshop on Artificial Intelligence and Statistics held in January 1993. These biennial workshops have succeeded in bringing together researchers from Artificial Intelligence and from Statistics to discuss problems of mutual interest. The exchange has broadened research in both fields and has strongly encour aged interdisciplinary work. The theme ofthe 1993 AI and Statistics workshop was: "Selecting Models from Data". The papers in this volume attest to the diversity of approaches to model selection and to the ubiquity of the problem. Both statistics and artificial intelligence have independently developed approaches to model selection and the corresponding algorithms to implement them. But as these papers make clear, there is a high degree of overlap between the different approaches. In particular, there is agreement that the fundamental problem is the avoidence of "overfitting"-Le., where a model fits the given data very closely, but is a poor predictor for new data; in other words, the model has partly fitted the "noise" in the original data.
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 504 | Sprache: Englisch | Produktart: Bücher | This volume is a selection of papers presented at the Fourth International Workshop on Artificial Intelligence and Statistics held in January 1993. These biennial workshops have succeeded in bringing together researchers from Artificial Intelligence and from Statistics to discuss problems of mutual interest. The exchange has broadened research in both fields and has strongly encour aged interdisciplinary work. The theme ofthe 1993 AI and Statistics workshop was: "Selecting Models from Data". The papers in this volume attest to the diversity of approaches to model selection and to the ubiquity of the problem. Both statistics and artificial intelligence have independently developed approaches to model selection and the corresponding algorithms to implement them. But as these papers make clear, there is a high degree of overlap between the different approaches. In particular, there is agreement that the fundamental problem is the avoidence of "overfitting"-Le., where a model fits the given data very closely, but is a poor predictor for new data; in other words, the model has partly fitted the "noise" in the original data.
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Learning from Data : Artificial Intelligence and Statistics V
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Ten years ago Bill Gale of AT&T Bell Laboratories was primary organizer of the first Workshop on Artificial Intelligence and Statistics. In the early days of the Workshop series it seemed clear that researchers in AI and statistics had common interests, though with different emphases, goals, and vocabularies. In learning and model selection, for example, a historical goal of AI to build autonomous agents probably contributed to a focus on parameter-free learning systems, which relied little on an external analyst's assumptions about the data. This seemed at odds with statistical strategy, which stemmed from a view that model selection methods were tools to augment, not replace, the abilities of a human analyst. Thus, statisticians have traditionally spent considerably more time exploiting prior information of the environment to model data and exploratory data analysis methods tailored to their assumptions. In statistics, special emphasis is placed on model checking, making extensive use of residual analysis, because all models are 'wrong', but some are better than others. It is increasingly recognized that AI researchers and/or AI programs can exploit the same kind of statistical strategies to good effect. Often AI researchers and statisticians emphasized different aspects of what in retrospect we might now regard as the same overriding tasks.
