1. Student Performance: Predict student performance in secondary education (high school).
2. Drug consumption (quantified): Classify type of drug consumer by personality data
3. Sports articles for objectivity analysis: 1000 sports articles were labeled using Amazon Mechanical Turk as objective or subjective. The raw texts, extracted features, and the URLs from which the articles were retrieved are provided.
4. Multimodal Damage Identification for Humanitarian Computing: 5879 captioned images (image and text) from social media related to damage during natural disasters/wars, and belong to 6 classes: Fires, Floods, Natural landscape, Infrastructural, Human, Non-damage.
5. A study of Asian Religious and Biblical Texts: Mainly from Project Gutenberg, we combine Upanishads, Yoga Sutras, Buddha Sutras, Tao Te Ching and Book of Wisdom, Book of Proverbs, Book of Ecclesiastes and Book of Ecclesiasticus
6. Speaker Accent Recognition: Data set featuring single English words read by speakers from six different countries for accent detection and recognition
7. Higher Education Students Performance Evaluation Dataset: The data was collected from the Faculty of Engineering and Faculty of Educational Sciences students in 2019. The purpose is to predict students' end-of-term performances using ML techniques.
8. Gender Gap in Spanish WP: Data set used to estimate the number of women editors and their editing practices in the Spanish Wikipedia