Datasets:

Modalities:
Text
Formats:
parquet
Languages:
English
Libraries:
Datasets
pandas
License:
nicholasKluge commited on
Commit
93dde34
·
verified ·
1 Parent(s): 3aec397

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +9 -60
README.md CHANGED
@@ -20,74 +20,23 @@ dataset_info:
20
  dataset_size: 563045
21
  language:
22
  - en
23
- pretty_name: Movielens-movies
24
  size_categories:
25
  - 1K<n<10K
26
  license: other
 
 
 
 
27
  ---
 
28
 
29
- # Movielens-movies
30
- This dataset contains a set of movies from the MovieLens website, a movie recommendation service.
31
 
32
- ## Overview
33
- MovieLens data sets were collected by the GroupLens Research Project at the University of Minnesota.
34
- The GroupLens Research has collected and made available rating data sets from the [MovieLens website](https://movielens.org).
35
- MovieLens 100K movie ratings contain 100,000 ratings(1-5)from 943 users on 1682 movies. Released 1998.
36
-
37
- ## Dataset Details
38
- The dataset from Kaggle is named [MovieLens100](https://www.kaggle.com/datasets/abhikjha/movielens-100k).
39
- Contains different CSV files for Movies, Ratings, Links, and Tags. We used only the file "movies.csv" in **movielens-movies dataset**.
40
-
41
- - Dataset Name: movielens-movies
42
- - Language: English
43
- - Total Size: 9,742 demonstrations
44
-
45
- **Citation:**
46
- ```latex
47
- @article{10.1145/2827872,
48
- author = {Harper, F. Maxwell and Konstan, Joseph A.},
49
- title = {The MovieLens Datasets: History and Context},
50
- year = {2015},
51
- issue_date = {January 2016},
52
- publisher = {Association for Computing Machinery},
53
- address = {New York, NY, USA},
54
- volume = {5},
55
- number = {4},
56
- issn = {2160-6455},
57
- url = {https://doi.org/10.1145/2827872},
58
- doi = {10.1145/2827872},
59
- journal = {ACM Trans. Interact. Intell. Syst.},
60
- month = dec,
61
- articleno = {19},
62
- numpages = {19},
63
- keywords = {Datasets, recommendations, ratings, MovieLens}
64
- }
65
- ```
66
- ## Contents
67
-
68
- The dataset consists of a data frame with the following columns:
69
-
70
- - **movieID** is a unique identifier of the rated movie.
71
- - **title:** the title of the rated movie with the release year in parentheses.
72
- - **genres:** a sequence of genres to which the rated movie belongs.
73
-
74
- ```bash
75
- {
76
- movieID: 2,
77
- title: "Jumanji (1995)",
78
- genres: "Adventure|Children|Fantasy"
79
- }
80
- ```
81
-
82
- ## How to use
83
 
84
  ```python
85
  from datasets import load_dataset
86
 
87
- dataset = load_dataset("AiresPucrs/movielens-movies", split='train')
88
-
89
  ```
90
-
91
- ## License
92
-
93
- This dataset is licensed under the USAGE LICENSE - [Other](https://files.grouplens.org/datasets/movielens/ml-100k-README.txt).
 
20
  dataset_size: 563045
21
  language:
22
  - en
23
+ pretty_name: MovieLens Movies
24
  size_categories:
25
  - 1K<n<10K
26
  license: other
27
+ task_categories:
28
+ - text-classification
29
+ tags:
30
+ - movies
31
  ---
32
+ # MovieLens Movies (Teeny-Tiny Castle)
33
 
34
+ 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.
 
35
 
36
+ ## How to Use
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
37
 
38
  ```python
39
  from datasets import load_dataset
40
 
41
+ dataset = load_dataset("AiresPucrs/movielens-movies", split = 'train')
 
42
  ```