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ISBN 10: 1092282297 ISBN 13: 9781092282291
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ISBN 10: 0443158886 ISBN 13: 9780443158889
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Idioma: Inglés
Publicado por Morgan Kaufmann (edition 5), 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
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Idioma: Inglés
Publicado por Elsevier Science & Technology, San Francisco, 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
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Añadir al carritoPaperback. Condición: 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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Idioma: Inglés
Publicado por Elsevier Science and Technology, US, 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de America
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Añadir al carritoPaperback. Condición: 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.
Idioma: Inglés
Publicado por Elsevier Science & Technology, 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
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Idioma: Inglés
Publicado por Elsevier Science and Technology, US, 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
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Añadir al carritoPaperback. Condición: 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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Añadir al carritoCondición: 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 .
Idioma: Inglés
Publicado por Elsevier Science and Technology, US, 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
EUR 102,98
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Añadir al carritoPaperback. Condición: 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.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 132,54
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Añadir al carritoPaperback. Condición: Brand New. 5th edition. 688 pages. 9.25x7.50x9.20 inches. In Stock.
Idioma: Inglés
Publicado por Elsevier Science & Technology, San Francisco, 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 138,32
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Añadir al carritoPaperback. Condición: 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.
Idioma: Inglés
Publicado por Elsevier Science and Technology, US, 2025
ISBN 10: 0443158886 ISBN 13: 9780443158889
Librería: Rarewaves.com UK, London, Reino Unido
EUR 107,73
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Añadir al carritoPaperback. Condición: 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.