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Añadir al carritoPaperback. Condición: As New. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
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EUR 32,93
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EUR 35,19
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Añadir al carritoCondición: 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.
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 44,03
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: INDOO, Avenel, NJ, Estados Unidos de America
EUR 46,37
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EUR 48,17
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
EUR 48,14
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Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 4 working days. 690.
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Publicado por Manning Publications, New York, 2023
ISBN 10: 1617297135 ISBN 13: 9781617297137
Idioma: Inglés
Librería: Grand Eagle Retail, Mason, OH, Estados Unidos de America
EUR 67,43
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Añadir al carritoPaperback. Condición: 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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EUR 50,33
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EUR 62,22
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EUR 56,28
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Publicado por Manning Publications 2023-06-09, 2023
ISBN 10: 1617297135 ISBN 13: 9781617297137
Idioma: Inglés
Librería: Chiron Media, Wallingford, Reino Unido
EUR 52,93
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Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 72,41
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Original o primera edición
EUR 63,48
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Añadir al carritoCondición: New. 2023. 1st Edition. Paperback. . . . . .
Publicado por Manning Publications, US, 2023
ISBN 10: 1617297135 ISBN 13: 9781617297137
Idioma: Inglés
Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de America
EUR 77,64
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Añadir al carritoPaperback. Condición: 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 34,19
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Librería: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, Alemania
EUR 56,70
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Añadir al carritoTaschenbuch. Condición: 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.
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 56,70
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Añadir al carritoTaschenbuch. Condición: 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 72,66
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EUR 56,70
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Añadir al carritoTaschenbuch. Condición: 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.
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
EUR 78,77
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Añadir al carritoCondición: New. 2023. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.
EUR 68,27
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Añadir al carritoPaperback. Condición: Brand New. 350 pages. 9.25x7.37x0.88 inches. In Stock.
EUR 49,35
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EUR 46,78
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Añadir al carritoKartoniert / Broschiert. Condición: 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 56,70
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Añadir al carritoTaschenbuch. Condición: 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.
Publicado por Manning Publications, New York, 2023
ISBN 10: 1617297135 ISBN 13: 9781617297137
Idioma: Inglés
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 90,24
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Añadir al carritoPaperback. Condición: 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 our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.