Deep Learning Recommender Systems
Deep Learning Recommender Systems
$64.99
USDRecommender 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.
- Explores the application of deep learning technology in recommendation systems, with plentiful real-life examples
- Introduces the development history of recommendation systems and the evolution diagram of recommendation models
- Teaches readers to effectively solve engineering problems, as well as developing understanding of the theoretical concepts
Reviews & endorsements
‘Recommender systems hold immense commercial value, and deep learning is taking them to the next level. This book focuses on real-world applications, equipping engineers with the tools to build smarter, more effective recommendation systems. With a clear and practical approach, this book is an essential guide to mastering the latest advancements in the field.’ Yue Zhuge, NGP Capital
‘Reading this book allows you to witness the wealth of resources and engineering practices driving recommendation system development. The authors share unique insights into bridging academic research and industry applications, providing valuable technical perspectives for practitioners and students. The book emphasizes innovative thinking and inspires readers to develop new solutions in recommendation system technologies.’ Zi Yang, Google DeepMind
Product details
May 2025Paperback
9781009447508
313 pages
244 × 170 × 17 mm
0.609kg
Available
Table of Contents
- 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.
