Applications Machine Learning Large Scale (10 results)

Condition: New.

paperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2025-05 Publisher: Tsinghua University Press 'Guided by two leading data scientists. this book will provide a systematic understanding of the latest advancements in LLM technology. teach theoretical knowledge. and enable you to responsibly integrate LLM into business scenarios. You will build an LLM-driven application. intuitively experience the framework's practical operation. and master knowledge points such as data version control. experiment tracking.…

Hardcover. Condition: new. Hardcover. Machine Learning (ML) has been widely applied to large-scale optimization and high-dimensional learning problems across industries and academic fields, helping solve complex challenges that traditional methods cannot easily address. In large-scale optimization, ML techniques tackle complex tasks involving massive data and variables, such as supply chain logistics optimization, industrial task scheduling, and ML algorithm parameter tuning, delivering more accurate results than conventional approaches. Additionally, ML is well-suited for multi-objective optimization problems-where multiple conflicting goals need simultaneous optimization-common in engineering, finance, and resource allocation. Furthermore, ML efficiently uncovers hidden patterns in high-dimensional data, supporting practical applications like marketing customer segmentation, anomaly detection, and image segmentation. Overall, ML's versatility makes it a key driver in advancing these fields, providing innovative solutions across professions. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

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

HRD. Condition: 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. Condition: new. Hardcover. Machine Learning (ML) has been widely applied to large-scale optimization and high-dimensional learning problems across industries and academic fields, helping solve complex challenges that traditional methods cannot easily address. In large-scale optimization, ML techniques tackle complex tasks involving massive data and variables, such as supply chain logistics optimization, industrial task scheduling, and ML algorithm parameter tuning, delivering more accurate results than conventional approaches. Additionally, ML is well-suited for multi-objective optimization problems-where multiple conflicting goals need simultaneous optimization-common in engineering, finance, and resource allocation. Furthermore, ML efficiently uncovers hidden patterns in high-dimensional data, supporting practical applications like marketing customer segmentation, anomaly detection, and image segmentation. Overall, ML's versatility makes it a key driver in advancing these fields, providing innovative solutions across professions. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …

Hardcover. Condition: new. Hardcover. Machine Learning (ML) has been widely applied to large-scale optimization and high-dimensional learning problems across industries and academic fields, helping solve complex challenges that traditional methods cannot easily address. In large-scale optimization, ML techniques tackle complex tasks involving massive data and variables, such as supply chain logistics optimization, industrial task scheduling, and ML algorithm parameter tuning, delivering more accurate results than conventional approaches. Additionally, ML is well-suited for multi-objective optimization problems-where multiple conflicting goals need simultaneous optimization-common in engineering, finance, and resource allocation. Furthermore, ML efficiently uncovers hidden patterns in high-dimensional data, supporting practical applications like marketing customer segmentation, anomaly detection, and image segmentation. Overall, ML's versatility makes it a key driver in advancing these fields, providing innovative solutions across professions. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. …

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Machine Learning (ML) has been widely applied to large-scale optimization and high-dimensional learning problems across industries and academic fields, helping solve complex challenges that traditional methods cannot easily address. In large-scale optimization, ML techniques tackle complex tasks involving massive data and variables, such as supply chain logistics optimization, industrial task scheduling, and ML algorithm parameter tuning, delivering more accurate results than conventional approaches. Additionally, ML is well-suited for multi-objective optimization problems-where multiple conflicting goals need simultaneous optimization-common in engineering, finance, and resource allocation. Furthermore, ML efficiently uncovers hidden patterns in high-dimensional data, supporting practical applications like marketing customer segmentation, anomaly detection, and image segmentation. Overall, ML's versatility makes it a key driver in advancing these fields, providing innovative solutions across professions.…

Hardcover. Condition: Brand New. 200 pages. 6.00x0.81x9.00 inches. In Stock. This item is printed on demand.

Buch. Condition: Neu. Applications of Machine Learning in Large-Scale Optimization and High-Dimensional Learning | Buch | Englisch | 2026 | MDPI AG | EAN 9783725890477 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…