The main purpose of Deep Dive Into Machine Learning is to ensure that you understand what machine learning can and cannot do for you right now, as well as what it may be able to do for you in the future. Despite the fact that it contains numerous code examples, you do not need to be a software engineer to use this textbook. Because this book addresses machine learning through arithmetic, you might come from any field with a strong emphasis on arithmetic. Rather than dealing with notions, you see the actual results of employing specific approaches to deal with huge amounts of data in exact ways in order to achieve a specific, practical conclusion.
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Paperback. Zustand: new. Paperback. The main purpose of Deep Dive Into Machine Learning is to ensure that you understand what machine learning can and cannot do for you right now, as well as what it may be able to do for you in the future. Despite the fact that it contains numerous code examples, you do not need to be a software engineer to use this textbook. Because this book addresses machine learning through arithmetic, you might come from any field with a strong emphasis on arithmetic. Rather than dealing with notions, you see the actual results of employing specific approaches to deal with huge amounts of data in exact ways in order to achieve a specific, practical conclusion. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9786207842421
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Taschenbuch. Zustand: Neu. DEEP DIVE INTO MACHINE LEARNING | Exploring Smart System | Chitransh Dixit (u. a.) | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207842421 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 130132428
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The main purpose of Deep Dive Into Machine Learning is to ensure that you understand what machine learning can and cannot do for you right now, as well as what it may be able to do for you in the future. Despite the fact that it contains numerous code examples, you do not need to be a software engineer to use this textbook. Because this book addresses machine learning through arithmetic, you might come from any field with a strong emphasis on arithmetic. Rather than dealing with notions, you see the actual results of employing specific approaches to deal with huge amounts of data in exact ways in order to achieve a specific, practical conclusion.Books on Demand GmbH, Überseering 33, 22297 Hamburg 184 pp. Englisch. Bestandsnummer des Verkäufers 9786207842421
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