Recommender Systems: Frontiers and Practices

This book provides a comprehensive guide to recommendation algorithms, covering traditional algorithms, deep learning, and practical experience with Microsoft's open-source project Microsoft Recommenders. It helps readers build accurate and efficient recommender systems from scratch.

Format: Hardback
Length: 280 pages
Publication date: 26 March 2024
Publisher: Springer Verlag, Singapore

This comprehensive book takes readers on a journey into the realm of recommendation algorithms, beginning with the foundational principles and core concepts of traditional algorithms. It delves into their strengths and limitations, providing a comprehensive understanding of their role in recommendation systems.

Next, the book transitions to the realm of deep learning, exploring the cutting-edge technology employed in recommender systems. It addresses the theoretical challenges and practical complexities that arise in this field, offering insights into the latest advancements and solutions.

To reinforce the theoretical knowledge, the book includes practical examples and case studies drawn from Microsoft's open-source project, Microsoft Recommenders. Readers can utilize the provided source code to gain hands-on experience in designing and implementing recommendation algorithms, enabling them to build robust and efficient recommender systems from scratch.

Throughout the book, clear explanations, diagrams, and code snippets make the content accessible and engaging, allowing readers to grasp the intricacies of recommendation algorithms with ease. Whether you are a software engineer, data scientist, or business professional interested in leveraging recommendation systems to enhance user experiences, this book is an invaluable resource for deepening your understanding and gaining practical skills.

Dimension: 235 x 155 (mm)
ISBN-13: 9789819989638