Artículos relacionados a Deep Learning Recommender Systems

Deep Learning Recommender Systems - Tapa blanda

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9781009447508: Deep Learning Recommender Systems
Tapa blanda
ISBN 10: 1009447505 ISBN 13: 9781009447508
Editorial: Cambridge University Press, 2025

Sinopsis

Recommender systems are ubiquitous in modern life and are one of the main monetization channels for Internet technology giants. This book helps graduate students, researchers and practitioners to get to grips with this cutting-edge field and build the thorough understanding and practical skills needed to progress in the area. It not only introduces the applications of deep learning and generative AI for recommendation models, but also focuses on the industry architecture of the recommender systems. The authors include a detailed discussion of the implementation solutions used by companies such as YouTube, Alibaba, Airbnb and Netflix, as well as the related machine learning framework including model serving, model training, feature storage and data stream processing.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca de los autores

Zhe Wang is an engineering director at Disney Streaming, leading a machine learning team. He has more than ten years of experience working in the field of recommender systems and computational advertising. He has published more than ten academic papers and three technical books, with more than 100,000 readers.

Chao Pu is a machine learning engineer with extensive experience in scalable machine learning system at large scale IT companies. He has designed, developed, operated and optimized multiple recommendation systems that serve millions of customers.

Felice Wang is a data scientist with a wealth of experience of creating analytics models, such as predicting customer retention and optimizing price. She has also implemented machine learning techniques to build data-driven resolutions for various business circumstances.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Cambridge University Press
Año de publicación
2025
Idioma
Inglés
ISBN 10 
1009447505
ISBN 13 
9781009447508
Encuadernación
Tapa blanda
Número de páginas
314
Contacto del fabricante
no disponible
Persona responsable
gpsr@libri.de
gpsr@libri.de

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