Introduction to Recommender Systems

Curious about how platforms suggest products or content you might like? This course demystifies the core principles behind recommender systems, explaining the underlying logic that powers personalization. You will gain a solid understanding of how these systems identify user preferences and drive engagement, transforming raw data into tailored experiences. What you'll learn: * Understand the fundamental concepts of recommender systems and their role in data science. * Explore different types of recommendation algorithms, including content-based and collaborative filtering. * Learn how to prepare and process data for building recommendation models. * Practice evaluating the performance of recommendation systems using key metrics. * Grasp the basics of modern approaches like hybrid systems and the ethical considerations in personalization. This course covers essential terminology, basic concepts, and foundational definitions before diving into practical applications. It is designed for beginners with no prior experience in recommender systems, requiring only a basic understanding of data concepts. Start building your knowledge of personalized recommendation technology today.