datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
GPU-Resources-Estimation-for-Deep-Learning-Training-Tasks
GPUMemNet and GPUUtilNet Dataset
This dataset accompanies the paper
“GPU Memory and Utilization Estimation for Training-Aware Resource
Management: Opportunities and Limitations.”
It contains synthetic deep learning training configurations and their measured
GPU memory consumption and utilization characteristics.
Dataset configurations
The dataset is divided into separate configurations because MLP, CNN, and
Transformer workloads use different feature schemas.… See the full description on the dataset page: https://huggingface.co/datasets/ehyo/GPU-Resources-Estimation-for-Deep-Learning-Training-Tasks.Obesity_Levels_Estimation
Estimation of Obesity Levels Based on Eating Habits and Physical Condition
Overview
This dataset is designed to estimate obesity levels based on several parameters including eating habits, physical condition, and lifestyle. It includes data from diverse individuals across different demographics, offering insights for research in healthcare, nutrition, and public health.
Dataset Characteristics
Type: Multivariate
Number of Instances: 2111
Number of Attributes:… See the full description on the dataset page: https://huggingface.co/datasets/naabiil/Obesity_Levels_Estimation.Wireless-Channel-Parameter-Estimation-Datasetautonomous-driving-driver-state-manifold-estimation-v0.1What this dataset tests
Whether a system can infer driver state
from cabin signals and driving context.
The output is a state manifold vector.
Not a single label.
Required outputs
driver_state_label
fatigue_score
distraction_score
agitation_score
confidence_estimate
state_transition_risk
Scoring conventions
all scores range 0 to 1
labels are baseline, fatigued, distracted, agitated, mixed
transition risk flags likelihood of deterioration in the next window
Use case
Layer one… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/autonomous-driving-driver-state-manifold-estimation-v0.1.aviation-pilot-vehicle-loop-coherence-state-estimation-v0.1What this dataset tests
Whether a system can estimate the coherenceof the pilot–aircraft control loopduring abnormal phases.
Key insightLoss of control beginswith loop misalignmentbefore any hard limits are exceeded.
Required outputs
loop_coherence_index
resonance_stability_band
control_lag_profile
correction_efficiency_score
baseline_deviation
Use case
Layer one of Pilot–Vehicle Loop Coherence Under Stress.Feeds attribution and adaptive intervention systems.
F1-driver-car-input-response-resonance-estimation-v0.1What this dataset tests
Whether a system can estimatedriver-car coupling resonance.
Focus
Phase locklatency matchinput smoothnessresponse gain stability
Required outputs
resonance score
phase lock index
latency match index
control smoothness ratio
response gain stability
All scores0 to 1
Highermeans better coupling.
hhs-covid-19-small-area-estimations-survey-monoval
HHS COVID-19 Small Area Estimations Survey - Monovalent Booster Audience - Wave 19
Description
The goal of the Monthly Outcome Survey (MOS) Small Area Estimations (SAE) are to generate estimates of the proportions of adults, by county and month, who were in the population of interest for the U.S. Department of Health and Human Services’ (HHS) We Can Do This COVID-19 Public Education Campaign. These data are designed to be used by practitioners and researchers to… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/hhs-covid-19-small-area-estimations-survey-monoval.EstimationDefoMap
EstimationDefoMap
tags: Computer Vision, Supervised Learning, Accuracy Assessment
Note: This is an AI-generated dataset so its content may be inaccurate or false
Dataset Description:
The 'EstimationDefoMap' dataset is designed for the task of defocus map estimation within computer vision applications, specifically focusing on supervised learning techniques. It contains a collection of images with corresponding defocus maps, which are used to train models to predict the level of… See the full description on the dataset page: https://huggingface.co/datasets/infinite-dataset-hub/EstimationDefoMap.hhs-covid-19-small-area-estimations-survey-primaryscores_estimationhhs-covid-19-small-area-estimations-survey-updated
HHS COVID-19 Small Area Estimations Survey - Updated Bivalent Vaccine Audience - Wave 27
Description
The goal of the Monthly Outcome Survey (MOS) Small Area Estimations (SAE) is to generate estimates of the proportions of adults, by county and month, who were in the population of interest for the U.S. Department of Health and Human Services’ (HHS) We Can Do This COVID-19 Public Education Campaign. These data are designed to be used by practitioners and researchers to… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/hhs-covid-19-small-area-estimations-survey-updated.usay-estimation