Unlock the Power of Recommendation: Discover the Recommender Systems Handbook

In the era of information overload, recommender systems have become indispensable tools for helping users navigate the vast sea of content and make informed decisions. From personalized movie recommendations to tailored product suggestions, recommender systems are shaping our online experiences and driving business outcomes.

The Recommender Systems Handbook is the definitive guide to this rapidly evolving field. Written by leading experts in the area, this comprehensive handbook provides a thorough overview of the fundamental concepts, techniques, and applications of recommender systems.

Recommender Systems Handbook

by Lior Rokach

4.4 out of 5

Language	:	English
File size	:	15000 KB
Text-to-Speech	:	Enabled
Enhanced typesetting	:	Enabled
Print length	:	1844 pages

FREE

Key Features of the Recommender Systems Handbook:

• In-depth coverage of all aspects of recommender systems, from data collection and preprocessing to evaluation and deployment.
• Written by leading experts in the field, providing authoritative insights and best practices.
• Over 100 real-world examples and case studies, illustrating the practical applications of recommender systems.
• Companion website with code, datasets, and additional resources.

Benefits of Reading the Recommender Systems Handbook:

• Gain a deep understanding of the fundamental concepts and techniques of recommender systems.
• Learn how to design, implement, and evaluate recommender systems for a variety of applications.
• Stay up-to-date on the latest research and developments in the field.
• Access a wealth of practical examples and case studies to help you apply your knowledge.

Who Should Read the Recommender Systems Handbook?

• Researchers and students in computer science, data science, and information systems.
• Practitioners who want to design, implement, or evaluate recommender systems.
• Business leaders who want to understand the potential of recommender systems for their organizations.

Table of Contents:

The Recommender Systems Handbook is divided into three parts:

1. Part I: Foundations
   • to Recommender Systems
   • Data Collection and Preprocessing
   • Evaluation of Recommender Systems
2. Part II: Techniques
   • Content-Based Recommender Systems
   • Collaborative Filtering Recommender Systems
   • Hybrid Recommender Systems
3. Part III: Applications
   • Recommender Systems for E-commerce
   • Recommender Systems for Social Media
   • Recommender Systems for Healthcare

Free Download Your Copy Today!

The Recommender Systems Handbook is available now in print and electronic formats. Free Download your copy today and unlock the power of recommendation!

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About the Authors:

• Lior Rokach is a Professor of Computer Science at Ben-Gurion University of the Negev, Israel. He is the author of several books and over 200 papers in the area of recommender systems.
• Bracha Shapira is a Professor of Computer Science at the University of Haifa, Israel. She is the author of several books and over 100 papers in the area of machine learning.
• Yoav Matias is a Principal Researcher at Google Research. He has published extensively in the area of recommender systems and is the inventor of several key algorithms used in Google's recommender systems.

Recommender Systems Handbook

by Lior Rokach

4.4 out of 5

Language	:	English
File size	:	15000 KB
Text-to-Speech	:	Enabled
Enhanced typesetting	:	Enabled
Print length	:	1844 pages

FREE