Publicado por Mercury Learning and Information, 2023
ISBN 10: 1683929497 ISBN 13: 9781683929499
Idioma: Inglés
Librería: Books From California, Simi Valley, CA, Estados Unidos de America
EUR 34,80
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Añadir al carritopaperback. Condición: Very Good.
Publicado por Mercury Learning and Information, 2023
ISBN 10: 1683929497 ISBN 13: 9781683929499
Idioma: Inglés
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 44,96
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Publicado por Mercury Learning and Information, 2023
ISBN 10: 1683929497 ISBN 13: 9781683929499
Idioma: Inglés
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 43,06
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Publicado por Mercury Learning and Information, 2023
ISBN 10: 1683929497 ISBN 13: 9781683929499
Idioma: Inglés
Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 50,84
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Publicado por Mercury Learning and Information, 2023
ISBN 10: 1683929497 ISBN 13: 9781683929499
Idioma: Inglés
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
EUR 62,64
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Publicado por Mercury Learning And Information, De Gruyter Dez 2023, 2023
ISBN 10: 1683929497 ISBN 13: 9781683929499
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 54,95
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -This book is designed for data scientists, machine learning practitioners, and anyone with a foundational understanding of Python 3.x. In the evolving field of data science, the ability to manipulate and understand datasets is crucial. The book offers content for mastering these skills using Python 3. The book provides a fast-paced introduction to 230 pp. Englisch.
EUR 54,95
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Añadir al carritoTaschenbuch. Condición: Neu. Python 3 and Feature Engineering | Oswald Campesato | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2023 | De Gruyter | EAN 9781683929499 | Verantwortliche Person für die EU: De Gruyter [9], Genthiner Str. 13, 10785 Berlin, orders[at]degruyter[dot]com | Anbieter: preigu.
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 54,95
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is designed for data scientists, machine learning practitioners, and anyone with a foundational understanding of Python 3.x. In the evolving field of data science, the ability to manipulate and understand datasets is crucial. The book offers content for mastering these skills using Python 3. The book provides a fast-paced introduction to a wealth of feature engineering concepts, equipping readers with the knowledge needed to transform raw data into meaningful information. Inside, you'll find a detailed exploration of various types of data, methodologies for outlier detection using Scikit-Learn, strategies for robust data cleaning, and the intricacies of data wrangling. The book further explores feature selection, detailing methods for handling imbalanced datasets, and gives a practical overview of feature engineering, including scaling and extraction techniques necessary for different machine learning algorithms. It concludes with a treatment of dimensionality reduction, where you'll navigate through complex concepts like PCA and various reduction techniques, with an emphasis on the powerful Scikit-Learn framework. 230 pp. Englisch.
Librería: moluna, Greven, Alemania
EUR 48,41
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Oswald Campesato (San Francisco, CA) specializes in Deep Learning, Python, and GPT-4. He is the author/co-author of over thirty-five books including Python 3 Using ChatGPT / GPT-4, NLP for Developers, and Artificial Intelligence, Machine Learning and Deep L.
Publicado por Mercury Learning And Information, Mercury Learning And Information, 2023
ISBN 10: 1683929497 ISBN 13: 9781683929499
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 63,76
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book is designed for data scientists, machine learning practitioners, and anyone with a foundational understanding of Python 3.x. In the evolving field of data science, the ability to manipulate and understand datasets is crucial. The book offers content for mastering these skills using Python 3. The book provides a fast-paced introduction to a wealth of feature engineering concepts, equipping readers with the knowledge needed to transform raw data into meaningful information. Inside, you'll find a detailed exploration of various types of data, methodologies for outlier detection using Scikit-Learn, strategies for robust data cleaning, and the intricacies of data wrangling. The book further explores feature selection, detailing methods for handling imbalanced datasets, and gives a practical overview of feature engineering, including scaling and extraction techniques necessary for different machine learning algorithms. It concludes with a treatment of dimensionality reduction, where you'll navigate through complex concepts like PCA and various reduction techniques, with an emphasis on the powerful Scikit-Learn framework.