Recommendation systems, also known as recommender systems, are algorithms and techniques used to predict user preferences and suggest items or content accordingly. By analyzing user data, such as past interactions, ratings, and behaviors, these systems can generate personalized recommendations that enhance user experience. There are various approaches to building recommendation systems, including collaborative filtering, content-based filtering, and hybrid methods that combine both. Commonly employed in e-commerce, streaming services, and social media platforms, recommendation systems play a crucial role in driving user engagement, increasing sales, and fostering user satisfaction by providing tailored content and product suggestions.