Fundamentals of recommendation systems

Recommendation systems, also known as recommender systems, are intelligent algorithms that are designed to predict and suggest items or content that users might find interesting or relevant. These systems analyze patterns in user behavior, preferences, and item characteristics to generate personalized recommendations. The primary purpose of recommendation systems is to enhance the user experience by providing relevant content, increasing user engagement and retention, driving sales and conversions in e-commerce platforms, facilitating content discovery in large item catalogs, and personalizing services across various domains. Recommendation systems play a crucial role in addressing the information overload problem by filtering and prioritizing content based on user preferences and behavior.

Recommendation systems have become an integral part of our digital experiences, influencing our choices in various domains, such as e-commerce, entertainment...