ISBN: 9783725866441 - data mining and machine learning in the era of big knowledge and large models (5 Ergebnisse)

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HRD. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Hardcover. Zustand: new. Hardcover. The present Reprint contains all 13 articles accepted and published in the Special Issue "Data Mining and Machine Learning in the Era of Big Knowledge and Large Models, 2026" of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory, models, algorithms and applications related to advancing data mining and machine learning in the current age. The topics of these articles focus on Transformer-based named entity recognition, knowledge recommendation, time series analysis, model integration, data quality improvement, hallucinations, and innovative application development. We hope that the Reprint will be both interesting and useful for those working in the area of data mining and machine learning, as well as for those with the proper mathematical background and a willingness to become familiar with recent advances in this field. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The present Reprint contains all 13 articles accepted and published in the Special Issue 'Data Mining and Machine Learning in the Era of Big Knowledge and Large Models, 2026' of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory, models, algorithms and applications related to advancing data mining and machine learning in the current age. The topics of these articles focus on Transformer-based named entity recognition, knowledge recommendation, time series analysis, model integration, data quality improvement, hallucinations, and innovative application development. We hope that the Reprint will be both interesting and useful for those working in the area of data mining and machine learning, as well as for those with the proper mathematical background and a willingness to become familiar with recent advances in this field.…