Recommendation algorithms are systems designed to suggest products, services, or content to users based on their preferences and behaviors. They analyze data from user interactions, such as clicks, purchases, or ratings, to identify patterns and make personalized recommendations. Commonly used by platforms like Netflix and Amazon, these algorithms enhance user experience by helping individuals discover items they may enjoy. There are various types of recommendation algorithms, including collaborative filtering and content-based filtering. Collaborative filtering relies on the preferences of similar users, while content-based filtering focuses on the attributes of items themselves. Together, these methods aim to improve user engagement and satisfaction.