See the power of a recommendation engine
Taylor and Jane both like watching movies. Taylor only likes dramas, comedies, and romances. Jane likes only action, adventure, and otherwise exciting films. One of the greatest benefits of ALS-based recommendation engines is that they can identify movies or items that users will like, even if they themselves think that they might not like them. Take a look at the movie ratings that Taylor and Jane have provided below. It would stand to reason that their different preferences would generate different recommendations.
This course touches on a lot of concepts you may have forgotten, so if you ever need a quick refresher, download the PySpark Cheat Sheet and keep it handy!
This exercise is part of the course
Building Recommendation Engines with PySpark
Exercise instructions
- Take a look at
TJ_ratings
using the.show()
method and any other methods you prefer to see how each of them rated the various movies they've seen. - Input user names into the
get_ALS_recs()
function provided to see what movies ALS recommends for Jane and Taylor based on the ratings provided. Do the ratings make sense to you?
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# View TJ_ratings
TJ_ratings.show()
# Generate recommendations for users
get_ALS_recs(["____","____"])