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Aggiungi al carrelloPaperback. Condizione: Brand New. 42 pages. 10.70x8.30x0.30 inches. In Stock.
Lingua: Inglese
Editore: Morgan Kaufmann (edition 5), 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
Da: BooksRun, Philadelphia, PA, U.S.A.
Paperback. Condizione: Very Good. 5. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
Lingua: Inglese
Editore: Morgan Kaufmann (edition 5), 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
Da: BooksRun, Philadelphia, PA, U.S.A.
Paperback. Condizione: Very Good. 5. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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Da: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
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Da: Majestic Books, Hounslow, Regno Unito
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Lingua: Inglese
Editore: Elsevier Science & Technology, San Francisco, 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. Data Mining: Practical Machine Learning Tools and Techniques Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Lingua: Inglese
Editore: Elsevier Science and Technology, US, 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
Da: Rarewaves USA, OSWEGO, IL, U.S.A.
Paperback. Condizione: New. **2026 Textbook and Academic Authors Association (TAA) Textbook Excellence "Texty" Award Winner**Data Mining: Practical Machine Learning Tools and Techniques, Fifth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated new edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including more recent deep learning content on topics such as generative AI (GANs, VAEs, diffusion models), large language models (transformers, BERT and GPT models), and adversarial examples, as well as a comprehensive treatment of ethical and responsible artificial intelligence topics. Authors Ian H. Witten, Eibe Frank, Mark A. Hall, and Christopher J. Pal, along with new author James R. Foulds, include today's techniques coupled with the methods at the leading edge of contemporary research.
Lingua: Inglese
Editore: Elsevier Science & Technology, 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 81,66
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Aggiungi al carrelloPaperback. Condizione: Brand New. 5th edition. 688 pages. 9.25x7.50x9.20 inches. In Stock.
Lingua: Inglese
Editore: Elsevier Science and Technology, US, 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 114,07
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Aggiungi al carrelloPaperback. Condizione: New. **2026 Textbook and Academic Authors Association (TAA) Textbook Excellence "Texty" Award Winner**Data Mining: Practical Machine Learning Tools and Techniques, Fifth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated new edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including more recent deep learning content on topics such as generative AI (GANs, VAEs, diffusion models), large language models (transformers, BERT and GPT models), and adversarial examples, as well as a comprehensive treatment of ethical and responsible artificial intelligence topics. Authors Ian H. Witten, Eibe Frank, Mark A. Hall, and Christopher J. Pal, along with new author James R. Foulds, include today's techniques coupled with the methods at the leading edge of contemporary research.
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EUR 81,80
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Aggiungi al carrelloCondizione: New. Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projectsPresents concrete tips and techniques for performance improvement that work by transforming .
Lingua: Inglese
Editore: Elsevier Science and Technology, US, 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
Da: Rarewaves USA United, OSWEGO, IL, U.S.A.
Paperback. Condizione: New. **2026 Textbook and Academic Authors Association (TAA) Textbook Excellence "Texty" Award Winner**Data Mining: Practical Machine Learning Tools and Techniques, Fifth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated new edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including more recent deep learning content on topics such as generative AI (GANs, VAEs, diffusion models), large language models (transformers, BERT and GPT models), and adversarial examples, as well as a comprehensive treatment of ethical and responsible artificial intelligence topics. Authors Ian H. Witten, Eibe Frank, Mark A. Hall, and Christopher J. Pal, along with new author James R. Foulds, include today's techniques coupled with the methods at the leading edge of contemporary research.
Da: Revaluation Books, Exeter, Regno Unito
EUR 131,10
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Aggiungi al carrelloPaperback. Condizione: Brand New. 5th edition. 688 pages. 9.25x7.50x9.20 inches. In Stock.
Lingua: Inglese
Editore: Elsevier Science & Technology, San Francisco, 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
Da: AussieBookSeller, Truganina, VIC, Australia
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Data Mining: Practical Machine Learning Tools and Techniques Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Lingua: Inglese
Editore: Elsevier Science and Technology, US, 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
Da: Rarewaves.com UK, London, Regno Unito
EUR 107,47
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Aggiungi al carrelloPaperback. Condizione: New. **2026 Textbook and Academic Authors Association (TAA) Textbook Excellence "Texty" Award Winner**Data Mining: Practical Machine Learning Tools and Techniques, Fifth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated new edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including more recent deep learning content on topics such as generative AI (GANs, VAEs, diffusion models), large language models (transformers, BERT and GPT models), and adversarial examples, as well as a comprehensive treatment of ethical and responsible artificial intelligence topics. Authors Ian H. Witten, Eibe Frank, Mark A. Hall, and Christopher J. Pal, along with new author James R. Foulds, include today's techniques coupled with the methods at the leading edge of contemporary research.