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Data Representation, Preprocessing, and Dimensionality Reduction provides a comprehensive introduction to the essential techniques used for preparing data for analytics, machine learning, and artificial intelligence applications. The book explores methods for representing structured and unstructured data, handling missing values, noise, and inconsistencies, and transforming raw data into meaningful formats. It also covers feature selection, feature extraction, normalization, encoding, and dimensionality reduction techniques such as PCA and other modern approaches. Through practical examples and real-world applications, the book demonstrates how effective data preprocessing and dimensionality reduction improve model performance, computational efficiency, and decision-making accuracy in data-driven environments.
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Data Representation, Preprocessing, and Dimensionality Reduction (Paperback)
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LAP Lambert Academic Publishing, 2026
ISBN 10: 6630237846
ISBN 13: 9786630237849
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Paperback. Condition: new. Paperback. Data Representation, Preprocessing, and Dimensionality Reduction provides a comprehensive introduction to the essential techniques used for preparing data for analytics, machine learning, and artificial intelligence applications. The book explores methods for representing structured and unstructured data, handling missing values, noise, and inconsistencies, and transforming raw data into meaningful formats. It also covers feature selection, feature extraction, normalization, encoding, and dimensionality reduction techniques such as PCA and other modern approaches. Through practical examples and real-world applications, the book demonstrates how effective data preprocessing and dimensionality reduction improve model performance, computational efficiency, and decision-making accuracy in data-driven environments. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9786630237849
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Data Representation, Preprocessing, and Dimensionality Reduction
Published by
LAP Lambert Academic Publishing, 2026
ISBN 10: 6630237846
ISBN 13: 9786630237849
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Softcover
Seller: California Books, Miami, FL, U.S.A.
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Condition: New. Seller Inventory # I-9786630237849
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Data Representation, Preprocessing, and Dimensionality Reduction
Published by
LAP LAMBERT Academic Publishing Jul 2026, 2026
ISBN 10: 6630237846
ISBN 13: 9786630237849
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 244 pp. Englisch. Seller Inventory # 9786630237849
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Data Representation, Preprocessing, and Dimensionality Reduction
Published by
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630237846
ISBN 13: 9786630237849
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Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data Representation, Preprocessing, and Dimensionality Reduction provides a comprehensive introduction to the essential techniques used for preparing data for analytics, machine learning, and artificial intelligence applications. The book explores methods for representing structured and unstructured data, handling missing values, noise, and inconsistencies, and transforming raw data into meaningful formats. It also covers feature selection, feature extraction, normalization, encoding, and dimensionality reduction techniques such as PCA and other modern approaches. Through practical examples and real-world applications, the book demonstrates how effective data preprocessing and dimensionality reduction improve model performance, computational efficiency, and decision-making accuracy in data-driven environments. Seller Inventory # 9786630237849
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Data Representation, Preprocessing, and Dimensionality Reduction
Published by
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630237846
ISBN 13: 9786630237849
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Taschenbuch
Seller: preigu, Osnabrück, Germany
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Taschenbuch. Condition: Neu. Data Representation, Preprocessing, and Dimensionality Reduction | Parveen Kumari (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630237849 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 136150734
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Data Representation, Preprocessing, and Dimensionality Reduction
Published by
LAP LAMBERT Academic Publishing Jul 2026, 2026
ISBN 10: 6630237846
ISBN 13: 9786630237849
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Data Representation, Preprocessing, and Dimensionality Reduction provides a comprehensive introduction to the essential techniques used for preparing data for analytics, machine learning, and artificial intelligence applications. The book explores methods for representing structured and unstructured data, handling missing values, noise, and inconsistencies, and transforming raw data into meaningful formats. It also covers feature selection, feature extraction, normalization, encoding, and dimensionality reduction techniques such as PCA and other modern approaches. Through practical examples and real-world applications, the book demonstrates how effective data preprocessing and dimensionality reduction improve model performance, computational efficiency, and decision-making accuracy in data-driven environments.OmniScriptum SRL, Str. Armeneasca 28/1, office 1, 2012 Chisinau 244 pp. Englisch. Seller Inventory # 9786630237849
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Data Representation, Preprocessing, and Dimensionality Reduction (Paperback)
Published by
LAP Lambert Academic Publishing, 2026
ISBN 10: 6630237846
ISBN 13: 9786630237849
New
Paperback
Seller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. Data Representation, Preprocessing, and Dimensionality Reduction provides a comprehensive introduction to the essential techniques used for preparing data for analytics, machine learning, and artificial intelligence applications. The book explores methods for representing structured and unstructured data, handling missing values, noise, and inconsistencies, and transforming raw data into meaningful formats. It also covers feature selection, feature extraction, normalization, encoding, and dimensionality reduction techniques such as PCA and other modern approaches. Through practical examples and real-world applications, the book demonstrates how effective data preprocessing and dimensionality reduction improve model performance, computational efficiency, and decision-making accuracy in data-driven environments. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9786630237849
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