Recommender Systems Complete Course Beginner to Advanced - Course Outline

This video tutorial covers the fundamentals of recommender systems, including their goals, processes, and the different generations. It explores the role of AI in recommender systems and discusses the challenges and applications. The course also delves into the fundamentals and taxonomy of recommender systems, item context, user rating matrix, and quality assessment. Evaluation techniques, both online and offline, are covered, along with content-based and collaborative filtering methods. The tutorial concludes with a transition to machine learning and deep learning topics.

Explain the fundamentals of recommender systems and their taxonomy.

What is the difference between content-based filtering and collaborative filtering?