Update README.md

README.md

@@ -23,66 +23,22 @@ dataset_info:
 license: other
 language:
 - en
-pretty_name: movielens-user-ratings
+pretty_name: MovieLens User Ratings
 size_categories:
 - 100K<n<1M
+task_categories:
+- text-classification
+tags:
+- movies
 ---
+# MovieLens User Ratings (Teeny-Tiny Castle)
 
-# Movielens-user-ratings
-This dataset contains a set of movie ratings from the MovieLens website, a movie recommendation service.
+This dataset is part of the tutorial tied to the [Teeny-Tiny Castle](https://github.com/Nkluge-correa/TeenyTinyCastle), an open-source repository containing educational tools for AI Ethics and Safety research. 
 
-## Overview 
-MovieLens data sets were collected by the GroupLens Research Project at the University of Minnesota.
-The GroupLens Research has collected and made available rating data sets from the [MovieLens website](https://movielens.org). 
-MovieLens 100K movie ratings contain 100,000 ratings(1-5)from 943 users on 1682 movies. Released 1998.
-
-## Dataset Details
-The dataset from Kaggle is named [MovieLens100](https://www.kaggle.com/datasets/abhikjha/movielens-100k). 
-Contains different CSV files for Movies, Ratings, Links, and Tags. We used only the file "ratings.csv" in **movielens-user-ratings dataset**.
-
-- Dataset Name: movielens-user-ratings
-- Language:  English
-- Total Size: 100,836 demonstrations
-
-**Citation:**
-```latex
-@article{10.1145/2827872,
-author = {Harper, F. Maxwell and Konstan, Joseph A.},
-title = {The MovieLens Datasets: History and Context},
-year = {2015},
-issue_date = {January 2016},
-publisher = {Association for Computing Machinery},
-address = {New York, NY, USA},
-volume = {5},
-number = {4},
-issn = {2160-6455},
-url = {https://doi.org/10.1145/2827872},
-doi = {10.1145/2827872},
-journal = {ACM Trans. Interact. Intell. Syst.},
-month = dec,
-articleno = {19},
-numpages = {19},
-keywords = {Datasets, recommendations, ratings, MovieLens}
-}
-```
-## Contents
-
-The dataset consists of a data frame with the following columns:
-
-- **userId:** a unique identifier of the user who made the rating.
-- **movieId:**  a unique identifier of the rated movie.
-- **rating:** the score of the rating on a five-star scale.
-- **timestamp:** the timestamp of the ratings.
-
-## How to use
+## How to Use
 
 ```python
 from datasets import load_dataset
 
-dataset = load_dataset("AiresPucrs/movielens-user-ratings", split='train')
-
+dataset = load_dataset("AiresPucrs/movielens-user-ratings", split = 'train')
 ```
-
-## License
-
-This dataset is licensed under the USAGE LICENSE - [Other](https://files.grouplens.org/datasets/movielens/ml-100k-README.txt).