In this [Netflix Prize](https://en.wikipedia.org/wiki/Netflix_Prize) assignment, participants need to predict a rating from a user (movie viewer) to a movie, i.e. rating|{user,movie}. See [🎦](https://youtu.be/ImpV70uLxyw), [🎦](https://youtu.be/8wLKuscyO9I). This problem is classified as a [**collaborative filtering**](https://en.wikipedia.org/wiki/Collaborative_filtering) and assumes latent dependency between users and movies. Recall that typically we build models which assume weak or no dependency between observations, unless we model time series, video frames, etc. 
 
This problem is unique due to the high sparsity of ratings. In the original Netflix problem, ~99% of ratings were missing, but here we have a subsample with 85% sparsity (if measured as a fraction of NaN values in the user×movie matrix. So, the challenge might be viewed as missing value imputation. We can also apply clustering and dimensions reduction solutions, which classify this problem as unsupervised learning. Also, we can apply supervised learning techniques, which learn from rating labels and predict missing values. However, the challenge is to derive users' features, since users have no explicit features in this dataset.
 
* HSE students model in R 
* JHU students model in Python. 
 
See **Rules** tab for more details.
 
## Acknowledgements
1. The original dataset was derived from [Netflix Movie Rating Dataset](https://www.kaggle.com/rishitjavia/netflix-movie-rating-dataset?select=Netflix_Dataset_Movie.csv), [Netflix Prize data](https://www.kaggle.com/netflix-inc/netflix-prize-data), [Netflix Prize Shows Information (9000 Shows)](https://www.kaggle.com/akashguna/netflix-prize-shows-information?select=imdb_processed.csv), [TMDB](https://www.themoviedb.org/?language=en-US) and [IMDB](https://www.imdb.com/interfaces).
1. The image is https://www.herox.com/blog/839-history-of-crowdsourcing-the-netflix-prize
1. **Competition Authors**. [HSE](https://hse.ru/) [ML Teaching Team](https://www.hse.ru/edu/courses/?filial=22723&lecturer=409923484&year=2021): [Oleg Melnikov](https://www.linkedin.com/in/olegmelnikov/), [Alexey Boldyrev](https://www.hse.ru/org/persons/223985242), [Vladimir Kirillin](https://www.hse.ru/org/persons/499313273), [Sergey Chervontsev](https://www.hse.ru/org/persons/305134539), Margarita Lazareva, Tatyana Yazykova, Mike Ovyan, Lika Lomidze, Vladimir Novikov, Valeriya Rogovchenko