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Machine Learning

General ML benchmarks, tabular data, AutoML, recommendation systems, anomaly detection, evaluation suites

192,282 datasets

Machine Learning

OSNI 1:1M Raster Map of Northern Ireland with Towns

A 1:1,000,000 scale raster map provides a cartographic overview of Northern Ireland, annotated with place names such as towns and cities. This static image dataset is published as open data by the Ordnance Survey of Northern Ireland (OSNI) and is suitable for use as a background layer. Its small scale makes it ideal for regional visualization rather than detailed local analysis.

ImageGeospatialJSONPlace NamesRaster MapNorthern IrelandComputer VisionBackground Mapping+1

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Machine Learning

OSNI 1:1Million Raster Map of Northern Ireland's Natural Environment

A 1:1,000,000 scale raster map provides a cartographic overview of Northern Ireland's natural environment. This static image is suitable for background mapping and is the smallest scale raster product from the Ordnance Survey of Northern Ireland. The dataset is published as open data under the Open Government Licence.

ImageGeospatialZIPJSONNatural EnvironmentRaster MapOpen Government DataNorthern IrelandComputer VisionBasemapGeospatial Raster+1

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Machine Learning

OSNI 10K Grid: Northern Ireland's 1:10,000 Scale Reference System

1058 tiles form a national grid reference system for Northern Ireland, with each tile covering 4.8 km x 3.2 km. The OSNI 1:10,000 raster grid is referenced to the Irish Grid, providing the naming convention for 1:10,000 scale mapping. It serves as a reference system for downloading the Digital Terrain Model and Mid Scale Raster map.

GeospatialCSVJSONCartographyGeospatial GridNorthern IrelandReference SystemOpen Data+1

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Machine Learning

Northern Ireland County Boundaries at 1:1 Million Scale

OSNI Open Data provides a 1:1,000,000 scale raster map depicting the county boundaries of Northern Ireland. This static image is the smallest-scale raster product from the Ordnance Survey of Northern Ireland, designed for use as a background map in desktop and web applications. The dataset is published under the Open Government Licence for reuse.

ImageGeospatialZIPJSONRaster MapCountiesNorthern IrelandAdministrative RegionsGeospatial BoundariesComputer VisionCounty Boundaries+1

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Machine Learning

OSNI 1:1 Million Raster Map of Northern Ireland Infrastructure

OSNI Open Data provides a 1:1,000,000 scale raster image depicting the infrastructure of Northern Ireland. This static map is the smallest-scale raster product from the Ordnance Survey of Northern Ireland, designed for use as a background layer in digital maps. Its availability under an open government license facilitates its integration into desktop and web-based geographic information systems.

ImageGeospatialZIPJSONRaster MapOpen Government DataNorthern IrelandComputer VisionGeospatial RasterSmall Scale MapNorthern Ireland InfrastructureInfrastructureBackground Mapping+1

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Machine Learning

OSNI 50K Grid: Northern Ireland Large-Scale Coverage Reference

The dataset provides a spatial index of 17,335 tiles covering all of Northern Ireland, referenced to the Irish Grid. It serves as a reference system for downloading the 50-meter Digital Terrain Model (DTM), with urban areas mapped at 1:1250 scale (0.6 km x 0.4 km tiles) and rural areas at 1:2500 scale (1.2 km x 0.8 km tiles). The grid is published for open data use and is available in multiple geospatial formats.

GeospatialCSVJSONGeospatial GridNorthern IrelandDigital Terrain ModelLarge ScaleReference SystemOpen Data+1

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Machine Learning

Global Impervious Surface Area Dynamics from Landsat Satellites, 1972-2019

A global impervious surface area (GISA) dataset maps human-built surfaces from 1972 to 2019 using over three million Landsat satellite images. Developed by Xin Huang at Wuhan University, it was validated with 120,777 independent reference sites from 270 cities worldwide, achieving an F-score of 0.954. The dataset provides the longest time span for global ISA mapping and was extracted from the entire global land area to reduce underestimation.

Time SeriesGeospatialUrban ExpansionImpervious SurfaceSatellite ImageryLand UseLarge Scale+1

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Machine Learning

US Take-Home Pay After Taxes for 51 Jurisdictions and 11 Income Levels, 2026

1,122 observations detail net pay after federal, state, and payroll taxes for the 2026 tax year. The data is computed by the StateTakeHome engine using official IRS, SSA, and state Department of Revenue publications, including 2026 legislative changes. Figures are provided for 11 gross income levels from $30,000 to $250,000 and two filing statuses across all 50 states and the District of Columbia.

TabularState ComparisonBenchmarkTax SimulationUs TaxationTake Home PayIncome Levels+1

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Machine Learning

Global Seasonal Mountain Snow Mask from MODIS MOD10A2

A global geospatial dataset provides a seasonal mountain snow mask derived from MODIS MOD10A2 snow cover and GTOPO30 elevation data at 30 arcsecond resolution. It includes three classifications: mountain snow presence, general snow cover, and cool-season cloud percentages. The data was produced by Melissa L. Wrzesien of the University of North Carolina at Chapel Hill for a manuscript submitted to Water Resources Research.

GeospatialGeospatial ClassificationMODISSnow CoverMountain Snow+1

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Machine Learning

Land Registry Application Counts for Northern Ireland, 2019-2020

The dataset contains counts of applications completed by the Land Registry of Northern Ireland's LPS Registrations during the 2019-2020 financial year. Data is categorized by six main application types, including dealings of whole properties, transfers of part, leases, first registrations, adverse possession claims, and deed rectifications. Figures include applications that were completed, abandoned, or withdrawn.

TabularCSVProperty RegistrationNorthern IrelandFinanceLand RegistryGovernment Administration+1

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Machine Learning

Crack Images with Annotated Masks for Digital Image Correlation Analysis

Crack images and corresponding annotated ground truth masks used to train, validate, and test a deep convolutional neural network for crack pixel detection. The data was created by Amir Hossein Rezaie of École Polytechnique Fédérale de Lausanne and is associated with publications from 2020 and 2021. The dataset is hosted on the paperswithcode platform.

ImageCrack DetectionCivil EngineeringImage SegmentationComputer VisionConstruction MaterialsDigital Image Correlation+1

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Machine Learning

Roundtrip: UCI and Image Benchmarks for Density Estimation

Datasets from the 'Roundtrip' paper provide a collection of UCI machine learning benchmarks and standard image datasets for evaluating deep generative models. The collection includes tabular data from domains such as activity recognition, protein structure, finance, audio, and particle physics, alongside the MNIST and CIFAR-10 image datasets. It is intended for benchmarking density estimation and generative modeling techniques across diverse data types.

TabularAudioMultimodalUci BenchmarksMachine Learning BenchmarkMultimodal DataFinanceDensity EstimationDeep Generative Models+1

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Machine Learning

A Library Of Nonconvex Bilevel Test Problems: AMPL Input Files

A growing collection of nonconvex bilevel test problems described in AMPL format, compatible with the BASBL solver. The library is authored by Remigijus Paulavičius of Imperial College London and includes problem statements, analysis, solutions, and input files. It is intended as a resource for researchers in the field.

TabularBilevel ProblemsAmpl FormatTest ProblemsNonconvex OptimizationMathematical Programming+1

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Machine Learning

Brisbane City Plan 2014: Future Parks and Community Facility Locations

Brisbane City Council's open data platform provides a geospatial dataset outlining future infrastructure for parks and community facilities. The feature class shows existing and future locations for park acquisition, upgrades, embellishments, and community facilities, categorized as specific or indicative. This data is part of the Brisbane City Plan 2014 and its Plans for Trunk Infrastructure.

GeospatialTrunk ParkNon Trunk ParkParks And Land For Community FacilitiesPftiInfrastructure PlanningLgipLocal Government Infrastructure PlanProperty And PlanningSpecific LocationUrban PlanningLocal GovernmentMaps And Spatial DataCommunity FacilityParksPlans For Trunk InfrastructureParks FacilitiesPcfBrisbane City Plan 2014+1

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Machine Learning

Nova Scotia Surplus Crown Property Auction Totals

Surplus Crown Property Auction Total Gross (Agent) records sales from public auctions of surplus government assets in Nova Scotia. The dataset covers items deemed to have no future government use and that cannot be economically refurbished. Columns suggest transaction details for each auction event, including location, fiscal year, and total gross sales.

TabularCSVXMLJSONSurplus Crown PropertyCrown PropertyPublic Asset DisposalFiscal DataSurplus Crown Property DisposalGovernment Auctions+1

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Machine Learning

City Plan 2014 LGIP PFTI: Brisbane Parks and Community Facilities Future Locations

Brisbane City Plan 2014 maps existing and future parks and community facilities infrastructure for local development planning. The dataset categorizes eight types of planned infrastructure, including specific and indicative locations for community facilities, park upgrades, and acquisitions. Brisbane City Council maintains this data, which was last updated on 2026-06-28.

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Machine Learning

Brisbane City Plan 2014: Future Parks and Community Facility Land Locations

Brisbane City Council's City Plan 2014 dataset shows existing and future locations for parks and community facilities infrastructure. The feature class includes eight categories such as community facilities and park upgrades, with both specific and indicative locations. This data is part of the Local Government Infrastructure Plan and Plans for Trunk Infrastructure mapping.

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Machine Learning

Brisbane City Plan 2014: Future Park and Community Facility Locations

Brisbane City Council's dataset maps existing and future locations for parks and community facilities as part of the Local Government Infrastructure Plan. The feature class includes categories such as specific and indicative locations for park acquisition, embellishment, upgrades, and community facilities. It is maintained by the Brisbane City Council and was last updated on 2026-06-28.

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Machine Learning

Brisbane City Plan 2014: Parks and Community Facilities Infrastructure Locations

Brisbane City Plan 2014 is the city's plan for future development, regularly updated with new information. This feature class shows existing and future Brisbane City Council LGIP Parks and Land for Community Facilities infrastructure, categorized into specific and indicative locations for community facilities, park acquisition, embellishment, upgrades, and corridor links. The dataset is provided by the Brisbane City Council and was last updated on 2026-06-28.

GeospatialTrunk ParkNon Trunk ParkParks And Land For Community FacilitiesPftiInfrastructure PlanningLocal Government Infrastructure PlanProperty And PlanningSpecific LocationUrban PlanningLocal GovernmentMaps And Spatial DataCommunity FacilityParksPlans For Trunk InfrastructureParks FacilitiesPcfBrisbane City Plan 2014+1

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Machine Learning

City Plan 2014 LGIP: Brisbane Parks and Community Facilities Future Locations

Brisbane City Plan 2014 is Brisbane City Council's plan for the future development of Brisbane. This feature class shows existing and future Brisbane City Council LGIP Parks and Land for Community Facilities infrastructure, including categories such as community facilities and park embellishments with specific or indicative locations. The dataset is maintained by Brisbane City Council and was last updated on 2026-06-28.

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