The dataset provided contains movie reviews given by NetFilm customers. Reviews were given between May 1996 and July 2014.
UserID – 4848 customers who provided a rating for each movie Movie 1 to Movie 206 – 206 movies for which ratings are provided by 4848 distinct users
- Viewers who have not watched the movies are not rated. These missing values are represented by NA. - Ratings are on a scale of -1 to 10 where -1 is the least rating and 10 is the best.
- Exploratory Data Analysis:
Which movies have maximum views/ratings?
What is the average rating for each movie? Define the top 5 movies with the maximum ratings.
Define the top 5 movies with the least audience.
- Recommendation Model: Some of the movies hadn’t been watched and therefore, are not rated by the Viewers. NetFilm would like to take this as an opportunity and build a machine learning recommendation algorithm which provides the ratings for each of the users.
Divide the data into training and test data
Build a recommendation model on training data
Make predictions on the test data
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