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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is collaborative filtering?
💡 Hint: Think about how Netflix recommends shows.
Question 2
Easy
What does the 'cold start problem' refer to?
💡 Hint: Consider new users on social media.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What technique is commonly used in recommendation systems to suggest products based on similar users?
- Matrix Factorization
- Collaborative Filtering
- Deep Learning
💡 Hint: Think about other users' preferences.
Question 2
True or False: The cold start problem presents no challenges for established users.
- True
- False
💡 Hint: Consider how long a user has been active.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design a product recommendation system for a new online bookstore. Discuss the techniques you would employ and how you would address the cold start problem.
💡 Hint: Consider how existing data can be leveraged and how to incorporate new information.
Question 2
Evaluate the impact of a sparse interaction matrix on the performance of a recommendation system. Propose potential solutions to mitigate these effects.
💡 Hint: Reflect on how data density influences accuracy.
Challenge and get performance evaluation