Morgan Kaufmann Publishers
Data Mining: Practical Machine Learning Tools and Techniques
Data Mining: Practical Machine Learning Tools and Techniques
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**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 researchAuthor: Ian H. Witten,Eibe Frank,Mark A. Hall
Binding Type: Paperback
Publisher: Morgan Kaufmann Publishers
Published: 04/01/2025
Pages: 688
Weight: 3.45lbs
Size: 9.20h x 7.10w x 1.30d
ISBN: 9780443158889
5th Edition
