Recommender Systems: Frontiers and Practices
by Dongsheng Li, Jianxun Lian, Le Zhang, Kan Ren, Tun Lu, Tao Wu and Xing Xie
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Fulfillment optionsRecommender Systems
This book starts from the classic recommendation algorithms, introduces readers to the basic principles and main concepts of the traditional algorithms, and analyzes their advantages and limitations. Then, it addresses the fundamentals of deep learning, focusing on the deep-learning-based technology used, and analyzes problems arising in the theory and practice of recommender systems, helping readers gain a deeper understanding of the cutting-edge technology used in these systems. Lastly, it shares practical experience with Microsoft 's open source project Microsoft Recommenders. Readers can learn the design principles of recommendation algorithms using the source code provided in this book, allowing them to quickly build accurate and efficient recommender systems from scratch.
Details
- Publisher
- Springer Nature Singapore
- Authors
- Dongsheng Li, Jianxun Lian, Le Zhang, Kan Ren, Tun Lu, Tao Wu, Xing Xie
- Format
- Paperback
- Published
- Mar 27, 2025
- ISBN-13
- 9789819989669
- Pages
- 280
- Printing
- Printed on demand
Recommender Systems for groups: pricing
Volume pricing applies automatically in your cart. No codes, no account needed.
| Copies | Price per copy | You save |
|---|---|---|
| 25 – 49 | $57.19 | 12% off list |
| 50 – 99 | $56.54 | 13% off list |
| 100+ | $55.89 | 14% off list |
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