Name: Data Mining: Practical Machine Learning Tools and Techniques (en Inglés)
Price: 305630.00 COP
Availability: InStock
Author: Ian H. Witten; Eibe Frank; Mark A. Hall; Christopher J. Pal; James Foulds Ph.D.
ISBN: 9780443158889

portada Data Mining: Practical Machine Learning Tools and Techniques (en Inglés)

Data Mining: Practical Machine Learning Tools and Techniques (en Inglés)

Formato

Libro Físico

Editorial

Morgan Kaufmann

Autor

Ian H. Witten; Eibe Frank; Mark A. Hall; Christopher J. Pal; James Foulds Ph.D.

Idioma

Inglés

N° páginas

688

Encuadernación

Tapa Blanda

ISBN13

9780443158889

N° edición

Data Mining: Practical Machine Learning Tools and Techniques (en Inglés)

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

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Reseña del libro "Data Mining: Practical Machine Learning Tools and Techniques (en Inglés)"

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