Recommender Systems: Frontiers and Practices by Dongsheng Li (.PDF)+

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File Size: 25.0 MB

Recommender Systems: Frontiers and Practices by Dongsheng Li, Jianxun Lian, Le Zhang, Kan Ren
Requirements: .ePUB, .PDF reader, 25.0 MB
Overview: 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. The emergence of Deep Learning has greatly changed the development of recommendation technology, and it is necessary for researchers and technicians in the field of recommender systems to have a deep understanding of deep learning-based recommendation technology.
Genre: Non-Fiction > Tech & Devices

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