Zhe Wang, Chao Pu, Felice Wang

Deep Learning Recommender Systems

• Broschiertes Buch

Produktbeschreibung

Recommender systems are ubiquitous in our lives and are one of the main monetization methods of the Internet. This book explores how to apply deep learning technology in recommender systems, helping practitioners and researchers to understand the engineering implementation solutions of industry giants and cutting-edge progress in the field.

Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 313
• Erscheinungstermin: 22. Mai 2025
• Englisch
• Abmessung: 244mm x 170mm x 17mm
• Gewicht: 542g
• ISBN-13: 9781009447508
• ISBN-10: 1009447505
• Artikelnr.: 72186981

Autorenporträt

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.

Inhaltsangabe

1. Growth engine of the internet - recommender system
2. Pre-deep learning era-the evolution of recommender systems
3. Top of the tide - application of deep learning in recommendation system
4. Application of embedding technology in recommender systems
5. Recommender systems from multiple perspectives
6. Engineering implementations in deep learning recommender systems
7. Evaluation in recommender systems
8. Frontier practice of deep learning recommender system
9. Build your own recommender system knowledge framework
Afterword.