11.4.1 - Nearest Neighbor Models
Enroll to start learning
You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Practice Questions
Test your understanding with targeted questions
What is the main function of Nearest Neighbor Models?
💡 Hint: Think about how recommendations work.
Name one similarity metric commonly used in Nearest Neighbor Models.
💡 Hint: What do we use to measure two things being alike?
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What does KNN stand for?
💡 Hint: What does the 'K' typically refer to in metrics?
True or False: Item-based collaborative filtering relies on similarities between users.
💡 Hint: Think about which group is being compared.
2 more questions available
Challenge Problems
Push your limits with advanced challenges
How would you address the cold start problem in a new recommender system using Nearest Neighbor Models?
💡 Hint: Consider how you can utilize user data before they engage with the system.
Explain how changes in K (the number of neighbors considered) could affect the quality of recommendations.
💡 Hint: Think about how varying K influences the local neighborhood around each user.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.