
# MovieLens User Ratings

This dataset contains ~1M user ratings, consisting of ~10k of the most recent movies from the MovieLens 25M dataset, for which over 30k unique users have rated. The dataset is streamed from the MovieLens 25M dataset, filters for the recent movies, and returns the user ratings for those. After a few joins and checks, we get this dataset. Included are the URLs of the respective movie posters.

The dataset is part of an example on [building a movie recommendation engine](https://www.pinecone.io/docs/examples/movie-recommender-system/) with vector search.
annotations_creators:machine-generated language_creators:machine-generated multilinguality:monolingual size_categories:100K<n<1M language:en movielens recommendation collaborative filtering region:us
{"annotations_creators": ["machine-generated"], "language_creators": ["machine-generated"], "language": ["en"], "license": [], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": [], "task_categories": [], "task_ids": [], "pretty_name": "MovieLens User Ratings", "tags": ["movielens", "recommendation", "collaborative filtering"]}
TAGS
#annotations_creators-machine-generated #language_creators-machine-generated #multilinguality-monolingual #size_categories-100K<n<1M #language-English #movielens #recommendation #collaborative filtering #region-us 


# MovieLens User Ratings

This dataset contains ~1M user ratings, consisting of ~10k of the most recent movies from the MovieLens 25M dataset, for which over 30k unique users have rated. The dataset is streamed from the MovieLens 25M dataset, filters for the recent movies, and returns the user ratings for those. After a few joins and checks, we get this dataset. Included are the URLs of the respective movie posters.

The dataset is part of an example on building a movie recommendation engine with vector search.
# MovieLens User Ratings

This dataset contains ~1M user ratings, consisting of ~10k of the most recent movies from the MovieLens 25M dataset, for which over 30k unique users have rated. The dataset is streamed from the MovieLens 25M dataset, filters for the recent movies, and returns the user ratings for those. After a few joins and checks, we get this dataset. Included are the URLs of the respective movie posters.

The dataset is part of an example on building a movie recommendation engine with vector search.
TAGS
#annotations_creators-machine-generated #language_creators-machine-generated #multilinguality-monolingual #size_categories-100K<n<1M #language-English #movielens #recommendation #collaborative filtering #region-us 
 # MovieLens User Ratings

This dataset contains ~1M user ratings, consisting of ~10k of the most recent movies from the MovieLens 25M dataset, for which over 30k unique users have rated. The dataset is streamed from the MovieLens 25M dataset, filters for the recent movies, and returns the user ratings for those. After a few joins and checks, we get this dataset. Included are the URLs of the respective movie posters.

The dataset is part of an example on building a movie recommendation engine with vector search.
passage: TAGS
#annotations_creators-machine-generated #language_creators-machine-generated #multilinguality-monolingual #size_categories-100K<n<1M #language-English #movielens #recommendation #collaborative filtering #region-us 
# MovieLens User Ratings

This dataset contains ~1M user ratings, consisting of ~10k of the most recent movies from the MovieLens 25M dataset, for which over 30k unique users have rated. The dataset is streamed from the MovieLens 25M dataset, filters for the recent movies, and returns the user ratings for those. After a few joins and checks, we get this dataset. Included are the URLs of the respective movie posters.

The dataset is part of an example on building a movie recommendation engine with vector search.