Practice Amazon - 11.8.2 | 11. Recommender Systems | Data Science Advance
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Amazon

11.8.2 - Amazon

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is item-to-item collaborative filtering?

💡 Hint: Think about how items relate to each other.

Question 2 Easy

Why is scalability important for Amazon's recommendation system?

💡 Hint: Consider the size of Amazon's product range.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What type of filtering does Amazon primarily use for recommendations?

User-based
Item-to-item
Content-based

💡 Hint: Focus on the relationship between items.

Question 2

Does Amazon's recommendation system change as new products are added?

True
False

💡 Hint: Think about the scalability of their system.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design an experiment to test the effectiveness of Amazon's recommendations compared to a generic recommendation algorithm.

💡 Hint: Think about how you'd measure users' engagement based on recommendations.

Challenge 2 Hard

Discuss potential ethical concerns with Amazon's recommendation systems, focusing on data privacy.

💡 Hint: Consider what users might want to know before their data is used.

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Reference links

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