CS 451 Quiz 24
Recommender systems and collaborative filtering
Email address *
According to Andrew Ng, recommender systems *
1 point
Suppose user j has watched movie i and rated it 4 out of 5. Which of the following describes this scenario? *
1 point
To learn the movie ratings for user j, we can use *
1 point
Collaborative filtering is an algorithm for *
1 point
One way to implement collaborative filtering is to alternate estimating theta's from x's, and x's from theta's. Which of the following algorithms operates in a similar way? *
1 point
Instead of alternating the two estimation problems, we can estimate x's and theta's jointly in a single minimization problem. *
1 point
Why do we initialize x's and theta's to small random values? *
1 point
In collaborative filtering we don't need to include "bias" features x0 = 1 and theta0 = 1 *
1 point
Which of the following is NOT one of movie titles used as examples? *
1 point
What comes to mind when you see this? *
1 point
Captionless Image
HW 5 teams [not graded] *
Please enter one of "working with [your partners name]", "working alone", or "still looking for a partner"
Your answer
Submit
Never submit passwords through Google Forms.
This content is neither created nor endorsed by Google. Report Abuse - Terms of Service