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Publicado por LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6207448766 ISBN 13: 9786207448760
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6207448766 ISBN 13: 9786207448760
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6207448766 ISBN 13: 9786207448760
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Añadir al carritoTaschenbuch. Condición: Neu. Machine learning using AI | Lilly Sheeba S. (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786207448760 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6207448766 ISBN 13: 9786207448760
Librería: Mispah books, Redhill, SURRE, Reino Unido
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Nov 2023, 2023
ISBN 10: 6207448766 ISBN 13: 9786207448760
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 104 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6207448766 ISBN 13: 9786207448760
Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Idioma: Inglés
Publicado por LAP Lambert Academic Publishing, 2023
ISBN 10: 6207448766 ISBN 13: 9786207448760
Librería: moluna, Greven, Alemania
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The book begins with an overview of the different types of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning. The authors then discuss the various data processing techniques that are essential for .
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Nov 2023, 2023
ISBN 10: 6207448766 ISBN 13: 9786207448760
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book begins with an overview of the different types of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning. The authors then discuss the various data processing techniques that are essential for machine learning, such as data cleaning, feature engineering, and model selection.In the following chapters, the book covers a wide range of machine learning topics, including:Regression: A technique for predicting continuous target values.Classification: A technique for predicting categorical target values.Clustering: A technique for grouping similar data points together.Dimensionality reduction: A technique for reducing the number of features in a dataset.Model evaluation: A technique for assessing the performance of a machine learning model.The book also includes a chapter on deep learning, which is a subfield of machine learning that has gained popularity in recent years.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6207448766 ISBN 13: 9786207448760
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 61,63
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book begins with an overview of the different types of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning. The authors then discuss the various data processing techniques that are essential for machine learning, such as data cleaning, feature engineering, and model selection.In the following chapters, the book covers a wide range of machine learning topics, including:Regression: A technique for predicting continuous target values.Classification: A technique for predicting categorical target values.Clustering: A technique for grouping similar data points together.Dimensionality reduction: A technique for reducing the number of features in a dataset.Model evaluation: A technique for assessing the performance of a machine learning model.The book also includes a chapter on deep learning, which is a subfield of machine learning that has gained popularity in recent years.