Essentials for Machine Learning (16 results)
Language: English
Published by Cambridge University Press, 2020
- Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Language: English
Published by Cambridge University Press, 2020
- Softcover
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Language: English
Published by Cambridge University Press, 2020
- Softcover
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Language: English
Published by Cambridge University Press, 2020
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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Language: English
Published by Cambridge University Press CUP, 2020
- Softcover
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Condition: New. 1st edition NO-PA16APR2015-KAP.
Language: English
Published by Cambridge University Press, 2020
- Softcover
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Condition: New. 2020. Paperback. . . . . .
Language: English
Published by Cambridge University Press, 2020
- Softcover
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Language: English
Published by Cambridge University Press, 2020
- Softcover
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Language: English
Published by Cambridge University Press, 2020
- Softcover
Seller: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
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Condition: New. 2020. Paperback. . . . . . Books ship from the US and Ireland.
Language: English
Published by Cambridge Univ Pr, 2020
- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Paperback. Condition: Brand New. 274 pages. 8.75x6.00x0.75 inches. In Stock.
Language: English
Published by Cambridge University Press, 2020
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - When machine learning engineers work with data sets, they may find the results aren't as good as they need. Instead of improving the model or collecting more data, they can use the feature engineering process to help improve results by modifying th…e data's features to better capture the nature of the problem. This practical guide to feature engineering is an essential addition to any data scientist's or machine learning engineer's toolbox, providing new ideas on how to improve the performance of a machine learning solution. Beginning with the basic concepts and techniques, the text builds up to a unique cross-domain approach that spans data on graphs, texts, time series, and images, with fully worked out case studies. Key topics include binning, out-of-fold estimation, feature selection, dimensionality reduction, and encoding variable-length data. The full source code for the case studies is available on a companion website as Python Jupyter not Elektronisches Buch.
Language: English
Published by Cambridge Univ Pr, 2020
- Softcover
- Print on Demand
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Paperback. Condition: Brand New. 274 pages. 8.75x6.00x0.75 inches. In Stock. This item is printed on demand.
Language: English
Published by Cambridge University Press, 2020
- Softcover
- Print on Demand
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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Language: English
Published by Cambridge University Press, 2020
- Softcover
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Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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Language: English
Published by Cambridge University Press, Cambridge, 2020
- Softcover
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Paperback. Condition: new. Paperback. When machine learning engineers work with data sets, they may find the results aren't as good as they need. Instead of improving the model or collecting more data, they can use the feature engineering process to help improve results by modifying the data's features to better capture the natu…re of the problem. This practical guide to feature engineering is an essential addition to any data scientist's or machine learning engineer's toolbox, providing new ideas on how to improve the performance of a machine learning solution. Beginning with the basic concepts and techniques, the text builds up to a unique cross-domain approach that spans data on graphs, texts, time series, and images, with fully worked out case studies. Key topics include binning, out-of-fold estimation, feature selection, dimensionality reduction, and encoding variable-length data. The full source code for the case studies is available on a companion website as Python Jupyter notebooks. This is a guide for data scientists who want to use feature engineering to improve the performance of their machine learning solutions. The book provides a unified view of the field, beginning with basic concepts and techniques, followed by a cross-domain approach to advanced topics, like texts and images, with hands-on case studies. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Language: English
Published by CAMBRIDGE, 2020
- Softcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This is a guide for data scientists who want to use feature engineering to improve the performance of their machine learning solutions. The book provides a unified view of the field, beginning with basic concepts and…techniques, followed by a cross-domain a.
