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Recommendation systems provide personalized suggestions to users from "summary" of Data Science for Business by Foster Provost,Tom Fawcett
Recommendation systems are algorithms that provide users with personalized suggestions based on their preferences and past interactions. These systems are widely used in e-commerce platforms, social media sites, and streaming services to help users discover new content that they may be interested in. By analyzing user data such as browsing history, purchase behavior, and ratings, recommendation systems can make accurate predictions about what items a user is likely to enjoy. One common type of recommendation system is a collaborative filtering system, which leverages the behavior of other users to make suggestions. Collaborative filtering works by identifying users who have similar preferences to a target user and recommending items that those similar users have liked. This approach is effective because it does not rely on explicit information about the items themselves, but rather on the pa...
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