Nearest Neighbor Collaborative Filtering

In this course, you will learn the fundamental techniques for making personalized recommendations through nearest-neighbor techniques. First you will learn user-user collaborative filtering, an algorithm that identifies other people with similar tastes to a target user and combines their ratings to make recommendations for that user. You will explore and implement variations of the user-user algorithm, and will explore the benefits and drawbacks of the general approach. Then you will learn the widely-practiced item-item collaborative filtering algorithm, which identifies global product associations from user ratings, but uses these product associations to provide personalized recommendations based on a user's own product ratings

• Understand collaborative filtering techniques for recommendations
• Apply user-user collaborative filtering algorithms
• Develop and test variations of filtering algorithms
• Analyze benefits and limitations of filtering approaches

• Basic computer and internet skills
• Ability to follow English instructions and complete practical exercises