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portada Data Mining: Practical Machine Learning Tools and Techniques
Type
Physical Book
Publisher
Author
Language
English
Pages
688
Format
Paperback
ISBN13
9780443158889
Edition No.
5

Data Mining: Practical Machine Learning Tools and Techniques

Ian H. Witten; Eibe Frank; Mark A. Hall; Christopher J. Pal; James Foulds Ph.d. (Author) · Morgan Kaufmann · Paperback

Data Mining: Practical Machine Learning Tools and Techniques - Ian H. Witten; Eibe Frank; Mark A. Hall; Christopher J. Pal; James Foulds Ph.D.

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Synopsis "Data Mining: Practical Machine Learning Tools and Techniques"

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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