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Añadir al carritoCondición: New. 1st edition NO-PA16APR2015-KAP.
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Añadir al carritoHardcover. Condición: New.
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Original o primera edición
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Añadir al carritoCondición: New. 2022. 1st Edition. hardcover. . . . . .
Idioma: Inglés
Publicado por Taylor and Francis Ltd, GB, 2022
ISBN 10: 1032193565 ISBN 13: 9781032193564
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 286,04
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Añadir al carritoHardback. Condición: New. This book provides a detailed description of machine learning algorithms in data analytics, data science life cycle, Python for machine learning, linear regression, logistic regression, and so forth. It addresses the concepts of machine learning in a practical sense providing complete code and implementation for real-world examples in electrical, oil and gas, e-commerce, and hi-tech industries. The focus is on Python programming for machine learning and patterns involved in decision science for handling data.Features:Explains the basic concepts of Python and its role in machine learningProvides comprehensive coverage of feature engineering including real-time case studiesPerceives the structural patterns with reference to data science and statistics and analyticsIncludes machine learning-based structured exercisesAppreciates different algorithmic concepts of machine learning including unsupervised, supervised, and reinforcement learningThis book is aimed at researchers, professionals, and graduate students in data science, machine learning, computer science, and electrical and computer engineering.
Librería: moluna, Greven, Alemania
EUR 240,60
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Añadir al carritoCondición: New. Dr. S. Sumathi is working as a Professor in the Department of Electrical and Electronics Engineering, PSG College of Technology, Coimbatore with teaching and research experience of 30 years. Her research interests include Neural Networks.
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Librería: preigu, Osnabrück, Alemania
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Añadir al carritoBuch. Condición: Neu. Machine Learning for Decision Sciences with Case Studies in Python | S. Sumathi (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2022 | CRC Press | EAN 9781032193564 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Idioma: Inglés
Publicado por Taylor and Francis Ltd, GB, 2022
ISBN 10: 1032193565 ISBN 13: 9781032193564
Librería: Rarewaves.com UK, London, Reino Unido
EUR 269,18
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Añadir al carritoHardback. Condición: New. This book provides a detailed description of machine learning algorithms in data analytics, data science life cycle, Python for machine learning, linear regression, logistic regression, and so forth. It addresses the concepts of machine learning in a practical sense providing complete code and implementation for real-world examples in electrical, oil and gas, e-commerce, and hi-tech industries. The focus is on Python programming for machine learning and patterns involved in decision science for handling data.Features:Explains the basic concepts of Python and its role in machine learningProvides comprehensive coverage of feature engineering including real-time case studiesPerceives the structural patterns with reference to data science and statistics and analyticsIncludes machine learning-based structured exercisesAppreciates different algorithmic concepts of machine learning including unsupervised, supervised, and reinforcement learningThis book is aimed at researchers, professionals, and graduate students in data science, machine learning, computer science, and electrical and computer engineering.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 334,19
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Añadir al carritoHardcover. Condición: Brand New. 400 pages. 10.00x7.00x1.65 inches. In Stock.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 226,40
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a detailed description of machine learning algorithms in data analytics, data science life cycle, Python for machine learning, linear regression, logistic regression, and so forth. It addresses the concepts of machine learning in a practical sense providing complete code and implementation for real-world examples in electrical, oil and gas, e-commerce, and hi-tech industries. The focus is on Python programming for machine learning and patterns involved in decision science for handling data.Features:Explains the basic concepts of Python and its role in machine learningProvides comprehensive coverage of feature engineering including real-time case studiesPerceives the structural patterns with reference to data science and statistics and analyticsIncludes machine learning-based structured exercisesAppreciates different algorithmic concepts of machine learning including unsupervised, supervised, and reinforcement learningThis book is aimed at researchers, professionals, and graduate students in data science, machine learning, computer science, and electrical and computer engineering. 478 pp. Englisch.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 276,49
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Añadir al carritoHardcover. Condición: Brand New. 400 pages. 10.00x7.00x1.65 inches. In Stock. This item is printed on demand.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 249,59
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Añadir al carritoBuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book provides a detailed description of machine learning algorithms in data analytics, data science life cycle, Python for machine learning, linear regression, logistic regression, and so forth. It addresses the concepts of machine learning in a practical sense providing complete code and implementation for real-world examples in electrical, oil and gas, e-commerce, and hi-tech industries. The focus is on Python programming for machine learning and patterns involved in decision science for handling data.Features:Explains the basic concepts of Python and its role in machine learningProvides comprehensive coverage of feature engineering including real-time case studiesPerceives the structural patterns with reference to data science and statistics and analyticsIncludes machine learning-based structured exercisesAppreciates different algorithmic concepts of machine learning including unsupervised, supervised, and reinforcement learningThis book is aimed at researchers, professionals, and graduate students in data science, machine learning, computer science, and electrical and computer engineering.