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Book synopsis

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.

Book details

Book category Books in German Naturwissenschaften, Medizin, Informatik, Technik Informatik, EDV Informatik

• Full title: Recommender Systems
• Author: Jianxun Lian, Le Zhang, Xing Xie, Tun Lu, Tao Wu, Kan Ren
• Language: English
• Binding: Paperback
• Number of pages: 296
• EAN: 9789819989669
• ISBN: 9819989663
• ID: 48877788
• Publisher: Springer Nature Singapore
• Weight: 452 g
• Dimensions: 235 × 155 × 17 mm
• Date of publishing: 27. March 2025

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