Making recommendations with SVD

Now that you have the recalculated matrix with all of its gaps filled in, the next step is to use it to generate predictions and recommendations.

Using calc_pred_ratings_df that you generated in the last exercise, with all rows and columns filled, find the movies that User_5 is most likely to enjoy.

Deze oefening maakt deel uit van de cursus

Building Recommendation Engines in Python

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Oefeninstructies

Find the highest ranked movies for User_5 by sorting all the reviews generated for User_5 from high to low.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# Sort the ratings of User 5 from high to low
user_5_ratings = ____.____[____,:].____(____=____)

print(user_5_ratings)

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