Databricks Exam Databricks-Certified-Professional-Data-Scientist Topic 5 Question 67 Discussion

Actual exam question for Databricks's Databricks Certified Professional Data Scientist Exam exam

Question #: 67
Topic #: 5

[All Databricks Certified Professional Data Scientist Exam Questions]

You are designing a recommendation engine for a website where the ability to generate more personalized recommendations by analyzing information from the past activity of a specific user, or the history of other users deemed to be of similar taste to a given user. These resources are used as user profiling and helps the site recommend content on a user-by-user basis. The more a given user makes use of the system, the better the recommendations become, as the system gains data to improve its model of that user. What kind of this recommendation engine is ?

ANaive Bayes classifier

BCollaborative filtering

CLogistic Regression

DContent-based filtering
Another aspect of collaborative filtering systems is the ability to generate more personalized recommendations by analyzing information from the past activity of a specific user, or the history of other users deemed to be of similar taste to a given user. These resources are used as user profiling and help the site recommend content on a user-by-user basis. The more a given user makes use of the system, the better the recommendations become, as the system gains data to improve its model of that user

Show Suggested Answer

Suggested Answer: B

by Billy at Aug 24, 2024, 09:14 PM

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Dorathy

15 days ago

I'm going with B) Collaborative filtering. Sounds like a textbook definition of this technique.

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1 months ago

I think the recommendation engine described is Collaborative filtering.

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