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In den WarenkorbPaperback. Zustand: As New. It's a preowned item in almost perfect condition. It has no visible cosmetic imperfections. May come without any shrink wrap; pages are clean and not marred by notes or folds of any kind.
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In den WarenkorbPaperback. Zustand: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
EUR 35,13
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In den WarenkorbZustand: very_good. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in very good condition! The cover and any other included accessories are also in very good condition showing some minor use. The spine is straight, there are no rips tears or creases on the cover or the pages.
EUR 43,95
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In den WarenkorbZustand: As New. Unread book in perfect condition.
EUR 46,29
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In den WarenkorbZustand: As New. Unread copy in mint condition.
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In den WarenkorbZustand: New.
EUR 46,30
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In den WarenkorbZustand: New.
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
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In den WarenkorbPAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Anbieter: THE SAINT BOOKSTORE, Southport, Vereinigtes Königreich
EUR 48,16
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In den WarenkorbPaperback / softback. Zustand: New. New copy - Usually dispatched within 4 working days. 690.
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EUR 48,14
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In den WarenkorbZustand: New.
Verlag: Manning Publications, New York, 2023
ISBN 10: 1617297135 ISBN 13: 9781617297137
Sprache: Englisch
Anbieter: Grand Eagle Retail, Mason, OH, USA
EUR 67,32
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In den WarenkorbPaperback. Zustand: new. Paperback. Many machine learning problems are too complex to be resolved by a single model or algorithm. Ensemble machine learning trains a group of diverse machine learning models to work together to solve a problem. By aggregating their output, these ensemble models can flexibly deliver rich and accurate results. Ensemble Methods for Machine Learning is a guide to ensemble methods with proven records in data science competitions and real world applications. Learning from hands-on case studies, you'll develop an under-the-hood understanding of foundational ensemble learning algorithms to deliver accurate, performant models. About the Technology Ensemble machine learning lets you make robust predictions without needing the huge datasets and processing power demanded by deep learning. It sets multiple models to work on solving a problem, combining their results for better performance than a single model working alone. This "wisdom of crowds" approach distils information from several models into a set of highly accurate results. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
EUR 59,46
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In den WarenkorbZustand: new.
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
EUR 50,34
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In den WarenkorbZustand: As New. Unread book in perfect condition.
EUR 62,11
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In den WarenkorbZustand: New.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 56,30
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In den WarenkorbZustand: New. In.
Verlag: Manning Publications 2023-06-09, 2023
ISBN 10: 1617297135 ISBN 13: 9781617297137
Sprache: Englisch
Anbieter: Chiron Media, Wallingford, Vereinigtes Königreich
EUR 52,94
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In den WarenkorbPaperback. Zustand: New.
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Erstausgabe
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In den WarenkorbZustand: New. 2023. 1st Edition. Paperback. . . . . .
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In den WarenkorbZustand: New.
EUR 77,50
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In den WarenkorbPaperback. Zustand: New. Many machine learning problems are too complex to be resolved by a single model or algorithm. Ensemble machine learning trains a group of diverse machine learning models to work together to solve a problem. By aggregating their output, these ensemble models can flexibly deliver rich and accurate results. Ensemble Methods for Machine Learning is a guide to ensemble methods with proven records in data science competitions and real world applications. Learning from hands-on case studies, you'll develop an under-the-hood understanding of foundational ensemble learning algorithms to deliver accurate, performant models. About the Technology Ensemble machine learning lets you make robust predictions without needing the huge datasets and processing power demanded by deep learning. It sets multiple models to work on solving a problem, combining their results for better performance than a single model working alone. This "wisdom of crowds" approach distils information from several models into a set of highly accurate results.
EUR 30,39
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In den WarenkorbZustand: as new. Wie neu/Like new.
Anbieter: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, Deutschland
EUR 56,70
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -Many machine learning problems are too complex to be resolved by a single model or algorithm. Ensemble machine learning trains a group of diverse machine learning models to work together to solve a problem. By aggregating their output, these ensemble models can flexibly deliver rich and accurate results. Ensemble Methods for Machine Learning is a guide to ensemble methods with proven records in data science competitions and real-world applications. Learning from hands-on case studies, you'll develop an under-the-hood understanding of foundational ensemble learning algorithms to deliver accurate, performant models. 350 pp. Englisch.
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
EUR 56,70
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -Many machine learning problems are too complex to be resolved by a single model or algorithm. Ensemble machine learning trains a group of diverse machine learning models to work together to solve a problem. By aggregating their output, these ensemble models can flexibly deliver rich and accurate results. Ensemble Methods for Machine Learning is a guide to ensemble methods with proven records in data science competitions and real-world applications. Learning from hands-on case studies, you'll develop an under-the-hood understanding of foundational ensemble learning algorithms to deliver accurate, performant models. 350 pp. Englisch.
EUR 56,70
Währung umrechnenAnzahl: 2 verfügbar
In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -Many machine learning problems are too complex to be resolved by a single model or algorithm. Ensemble machine learning trains a group of diverse machine learning models to work together to solve a problem. By aggregating their output, these ensemble models can flexibly deliver rich and accurate results. Ensemble Methods for Machine Learning is a guide to ensemble methods with proven records in data science competitions and real-world applications. Learning from hands-on case studies, you'll develop an under-the-hood understanding of foundational ensemble learning algorithms to deliver accurate, performant models.
EUR 72,68
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In den WarenkorbZustand: New.
EUR 78,64
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In den WarenkorbZustand: New. 2023. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.
EUR 49,36
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In den WarenkorbZustand: NEW.
EUR 46,78
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In den WarenkorbKartoniert / Broschiert. Zustand: New. Über den AutorrnrnGautam Kunapuli has over 15 years of experience in academia and the machine learning industry. He has developed several novel algorithms for diverse application domains including social network analysis, text and natu.
EUR 68,88
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In den WarenkorbPaperback. Zustand: Brand New. 350 pages. 9.25x7.37x0.88 inches. In Stock.
EUR 79,38
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In den WarenkorbPaperback. Zustand: Brand New. 350 pages. 9.25x7.37x0.88 inches. In Stock.
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
EUR 56,70
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -Many machine learning problems are too complex to be resolved by a single model or algorithm. Ensemble machine learning trains a group of diverse machine learning models to work together to solve a problem. By aggregating their output, these ensemble models can flexibly deliver rich and accurate results. Ensemble Methods for Machine Learning is a guide to ensemble methods with proven records in data science competitions and real-world applications. Learning from hands-on case studies, you'll develop an under-the-hood understanding of foundational ensemble learning algorithms to deliver accurate, performant models.Manning, St.-Martin-Straße 82, 81541 München 350 pp. Englisch.