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Student performance, MOOC logs, knowledge tracing, standardized tests, learning analytics
13,874 datasets
60,000 32x32 color images categorized into 10 mutually exclusive classes including animals and vehicles. The dataset is split into 50,000 training images and 10,000 test images, provided as Python-compatible pickle files for deep learning frameworks.
Employee salary records for a single company. The data focuses on individual compensation figures to support predictive modeling of earnings.
95,000+ audio recordings across 'fake' and 'real' speech categories are provided in four distinct preprocessing versions. The collection includes human speech from the Arctic dataset paired with synthetic versions generated by multiple text-to-speech algorithms.
480 student records across three performance categories (Low, Medium, High) based on 16 behavioral and demographic features. The data tracks classroom engagement metrics such as hand-raising and resource visits alongside parental involvement indicators.
Processed data from the Chem-prop-pred GitHub repository, hosted on Hugging Face by author eamag. The dataset was last updated on January 4, 2026. Platform tags indicate it is likely used for property prediction tasks in chemistry and graph machine learning.
Approximately 600 million tokens and 405,000 examples make up this large-scale dataset for competitive exam preparation and reasoning AI. Generated using advanced distillation techniques, it covers over 25 Indian and international examinations including JEE, NEET, UPSC, Banking, GRE, and IELTS. The dataset was created by shravan01 and last updated on December 15, 2025.
A curated dataset of 3,633 knowledge rows designed to train an AI assistant for Title IX guidance. It was created by author 'carseng' and last updated on December 8, 2025. The content is distilled from OCR Q&A documents and Federal Register commentary related to Title IX (2020 regulations), FERPA, ADA, Section 504, VAWA, and the Clery Act.
Comprising mathematical competition problems specifically curated for the third progress prize of the AI Mathematical Olympiad (AIMO). It provides a benchmark for evaluating the reasoning and problem-solving capabilities of AI models in the context of high-level mathematics.
data.delaware.gov provides a dataset on student enrollment and absenteeism for Delaware schools. The data includes counts of actively enrolled students, average days enrolled and absent, and the percentage of students deemed chronically absent per school year. Columns allow analysis by school, district, grade, race, gender, and other demographic subgroups.
Meta Open Materials 2024 (OMat24) is a dataset for materials science and chemistry research, released by Facebook. The dataset is designed to be used with the FAIRChem package, which suggests a focus on standardized, accessible data for computational chemistry. It was last updated on the platform in December 2025.
2013-2019 attendance and chronic absenteeism data for New York City schools, aggregated at the city, borough, district, and individual school levels. The dataset is hosted on the NYC Open Data platform (data.cityofnewyork.us) and was last updated in November 2025. It includes counts and percentages for days present, absent, and chronic absenteeism, broken down by grade and demographic categories.
MLMI2-CSSI developed Foundry to provide a collection of machine-learning ready datasets specifically for materials science and chemistry. Updated in January 2026, the repository serves as a discovery hub to bridge the gap between raw scientific data and model-ready inputs.
FinePDFs-Edu dataset consists of over 350 billion tokens of educational text extracted from PDFs. The dataset was created by Web3Survivor using an educational quality classifier trained on annotations from a large language model to filter content from the broader FinePDFs collection. It covers 69 languages and was last updated on December 11, -0001.
A dataset of 2,200 prompts designed to elicit deep reasoning across math, coding, precise instruction following, and general chat. It was created by the mlx-community to train the Olmo-3-7B-Think model and was last updated on November 21, 2025. The dataset blends high-quality curated sources with filtering for deliberate reasoning and is converted for compatibility with MLX-LM-LoRA.
Washington state data estimates childcare demand and supply gaps for children from infancy through age 12. The Department of Children, Youth, and Families (DCYF) estimates families of about 293,000 pre-school children and over 491,000 school-age children need care, with licensed or subsidized services meeting only 27% and 12% of that need respectively. The dataset was last updated in September 2025.
Information compiled for the CIVE3207 (ARCN4100) Historic Site Recording and Assessment course in 2025. Undergraduate students of the Architectural Conservation and Sustainability Program at Carleton University will use these data to produce a Heritage Recording of this important Site. The dataset was authored by Adam Weigert and last updated on December 27, 2025.
1,309 passenger records from the 1912 shipwreck categorized by survival status and demographic details. The data includes 12 distinct variables such as passenger class, age, and family relations to support binary classification modeling.
University Medical Center Groningen data likely contains medical or clinical research information. The dataset is hosted on the Papers with Code platform, which suggests a connection to computational research. Specific details about its size, format, and creation date are unknown.
Cleanlab is an open-source library for data-centric AI and machine learning quality, developed by the Cleanlab organization and updated through January 2026. It provides a standardized package for identifying and fixing issues in messy, real-world datasets and labels.
Featuring the survey instruments used in a 2022 research project at Rotterdam University of Applied Sciences to measure perceived data literacy among business programme students and lecturers. The questionnaires operationalize data literacy across six core competencies: awareness, access, engagement, management, communication, and use. The instruments include full item lists, Likert-scale response structures, and demographic questions.