Published by Mercury Learning and Information, 2023
ISBN 10: 1683929497 ISBN 13: 9781683929499
Language: English
Seller: Books From California, Simi Valley, CA, U.S.A.
paperback. Condition: Very Good.
Published by Mercury Learning and Information, 2023
ISBN 10: 1683929497 ISBN 13: 9781683929499
Language: English
Seller: California Books, Miami, FL, U.S.A.
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Published by Mercury Learning and Information, 2023
ISBN 10: 1683929497 ISBN 13: 9781683929499
Language: English
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Published by Mercury Learning and Information, 2023
ISBN 10: 1683929497 ISBN 13: 9781683929499
Language: English
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
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Published by Mercury Learning and Information, 2023
ISBN 10: 1683929497 ISBN 13: 9781683929499
Language: English
Seller: Kennys Bookstore, Olney, MD, U.S.A.
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Published by Mercury Learning And Information, De Gruyter Dez 2023, 2023
ISBN 10: 1683929497 ISBN 13: 9781683929499
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Add to basketTaschenbuch. Condition: 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.
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Add to basketTaschenbuch. Condition: 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.
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Add to basketTaschenbuch. Condition: 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.
Published by Mercury Learning And Information, De Gruyter, 2023
ISBN 10: 1683929497 ISBN 13: 9781683929499
Language: English
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Add to basketTaschenbuch. Condition: 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.
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Add to basketCondition: 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.