000			01710 a2200217 4500
005			20251017231004.0
020			_a9780443158889
082			_a 005.74 WIT
100			_aWitten, Ian H.
245			_aData Mining: Practical Machine Learning Tools And Techniques
250			_a5
260			_bElsevier, Morgan Kaufmann _aCambrige _c2016
300			_a760
520			_aData 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
650			_aData Mining
650			_aMachine Learning
700			_aFrank, Eibe
700			_aHall, Mark A
700			_aPal, Christopher J
942			_cBK _2ddc
999			_c51845 _d51845