19,997 machine learning datasets
19,997 dataset results
MmCows is a large-scale multimodal dataset for behavior monitoring, health management, and dietary management of dairy cattle.
Concrete is the most important material in civil engineering. The concrete compressive strength is a highly nonlinear function of age and ingredients.
This dataset contains demographic and personal health information for individuals, along with the corresponding medical insurance charges billed to them. It is commonly used to build predictive models for insurance costs and to explore relationships between factors such as age, BMI, smoking status, and region on medical expenses.
Dataset consists of scores of 384,977 students in the Mathematics, Physics, and Chemistry sections of 2009 IIT-JEE (The Joint Entrance Exam of Indian Institutes of Technology), along with their gender, birth category, disability status, and zip code.
To check the validity of the ai4st ontology, an adapted, lightweight systematic literature review (SLR) was conducted to analyse related research. This SLR protocol was followed:
The works-magnet aims at getting visible the AI-processed metadata for scholarly outputs and help curators improve those metadata. This dataset lists all the corrections asked by the works-magnet users to improve OpenAlex affiliations metadata.
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Thunder-NUBench (Negation Understanding Benchmark) is a benchmark specifically designed to evaluate large language models’ (LLMs) sentence-level understanding of negation. Thunder-NUBench introduces rich, manually curated sentence pairs and multiple-choice tasks that contrast standard negation with structurally similar distractors (e.g., local negation, contradiction, paraphrase). The goal is to probe semantic-level understanding of negation.
Ref-AVS seeks to segment objects within the visual domain based on expressions containing multimodal cues.
A dataset of German parliament debates covering 74 years of plenary protocols across all 16 state parliaments of Germany as well as the German Bundestag. The debates are separated into individual speeches which are enriched with meta data identifying the speaker as a member of the parliament (mp).
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distillation and psychological sft using only one dataset data statement psychological knowledge : general knowledge ≈ 4 : 10 (precise num is 3868 : 10000)
<span style="color: red;">Warning: this dataset contains data that may be offensive or harmful. The data are intended for research purposes, especially research that can make models less harmful.</span>
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DynOPETs is a real-world RGB-D dataset designed for object pose estimation and tracking in dynamic scenes with moving cameras. COPE119 119 sequences covering 6 common categories from the COPE benchmark: bottles, bowls, cameras, cans, laptops, mugs. Designed for COPE (Category-level Pose Estimation) methods.
Please refer to the Zenodo page for a detailed description: https://zenodo.org/records/15665101