Recommendations from binary data

So you see from the ROEM, these models can still generate meaningful test predictions. Let's look at the actual recommendations now.

The col function from the pyspark.sql.functions class has been imported for you.

100 XP

The dataframe original_ratings is provided for you. It contains the original ratings that users provided. Use .filter() to examine user 26's original ratings.
The dataframe binary_recs is also provided. It contains the recommendations for each user. Use .filter() to examine userId == 26 recommendations. Do they seem consistent with the recommendations the model provided?
Do the same thing with user 99. Feel free to examine other users.