Hands on Implementation Machine Learning by Kumar Tipu (11 results)
- Softcover
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Taschenbuch. Condition: Neu. Hands-On Implementation of Machine Learning Models | Rupesh Kumar Tipu | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207805945 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | A…nbieter: preigu.
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PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Language: English
Published by LAP LAMBERT Academic Publishing Jun 2024, 2024
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 76 pp. Englisch.
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Language: English
Published by LAP LAMBERT Academic Publishing Jun 2024, 2024
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -'Hands-On Implementation of Machine Learning Models' is a practical guide designed to bridge the gap between machine learning theory and real-world applications. It provides clear explanations of fundamental and advanced machine learnin…g models, including linear and logistic regression, decision trees, support vector machines, k-means clustering, PCA, hierarchical clustering, random forests, gradient boosting machines, and neural networks.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch.
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 'Hands-On Implementation of Machine Learning Models' is a practical guide designed to bridge the gap between machine learning theory and real-world applications. It provides clear explanations of fundamental and advanced machine learning… models, including linear and logistic regression, decision trees, support vector machines, k-means clustering, PCA, hierarchical clustering, random forests, gradient boosting machines, and neural networks.
