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787 datasets for “machine learning”
- data.gov.au
High resolution conductivity mapping using regional AEM survey and machine learning
Geoscience Australia DataUpdated 16 Oct 2025
… We use a gradient boosted tree machine learning algorithm to discover relationships between AEM conductivity models across northern …
- Data.gov Catalog
Challenge Round 0 (Dry Run) Test Dataset
National Institute of Standards and TechnologyUpdated 4 Feb 2020
This dataset was an initial test harness infrastructure test for the TrojAI program. It should not be used …
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- data.gov.au
Australian Phytoplankton Microscopy Machine Learning Dataset
CSIRO Data Access PortalUpdated 11 Nov 2026
The Australian Phytoplankton Microscopy Machine Learning Dataset is an annotated collection of laboratory microscopy imagery developed to support …
- GovData Germany
Self-attention for raw optical Satellite Time Series Classification
open.bydataUpdated 14 Nov 2026
… This dataset was used to compare several deep learning models on preprocessed satellite data to industry standards with …
- Data.gov Catalog
Dataset of channels and received IEEE 802.11ay signals for sensing applications in the 60GHz band
National Institute of Standards and TechnologyUpdated 27 May 2021
… The dataset is suitable for development and testing of machine/deep learning algorithms. The dataset can be used …
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- VND.MS-EXCEL
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- data.gov.au
National Gravity and Magnetic Derivatives Customised for Data Analysis and Machine Learning
Geoscience Australia DataUpdated 16 Oct 2025
… Various Fast Fourier Transforms (FFT) were applied to each grid (see ‘Grids_for_Machine_Learning_dataset_notes.pdf …
- TIF
- Opendatasoft hubLive preview
Spectres infrarouge OPTIR de bactéries lactiques
Lagneaux, PaulUpdated 7 Apr 2026
Lien vers la fiche source Infrared OPTIR (Optical Photothermal InfraRed) spectra of 13 strains of lactic acid bacteria …
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- ODS API
- GovData Germany
DL Surrogates, Training Data Set (8640 samples)
open.bydataUpdated 14 Nov 2026
… minimum drag profiles in laminar flow using deep learning surrogates. Full details are given at: https://github.com …
- Opendatasoft hubLive preview
AMPERE: Détection et diagnostic des défauts rotorique et statorique des machines tournantes
Soualhi, MoncefUpdated 20 Aug 2025
Lien vers la fiche source Dataset of speed, current, voltage and vibration measurements of an electromechanical drive system …
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- JSON
- GEOJSON
- ODS API
- Opendatasoft hubLive preview
Expression and gene network datasets for benchmarking phenotype prediction
Brouard, CélineUpdated 19 Dec 2023
Lien vers la fiche source Companion simulated dataset for the preprint "Should we really use graph neural networks …
- CSV
- JSON
- GEOJSON
- ODS API
- Open Government Canada
Algorithmic Impact Assessment - Employment Insurance Machine Learning Workload
Employment and Social Development Canada | Emploi et Développement social CanadaUpdated 21 Nov 2024
## EI Machine Learning Workload: Achieving Workload Reduction in Employment Insurance Recalculation Processes Recalculation within the context of Employment …
- JSON
- Data.gov Catalog
Artificial Intelligence for Robust Integration of AMI and Synchrophasor Data to Significantly Boost Solar Adoption
Arizona State UniversityUpdated 16 Apr 2025
The overarching goal of the project is to create a highly efficient framework of machine learning (ML) methods …
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- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 16 Oct 2025
In this study, we aim to identify the most appropriate methods for spatial interpolation of seabed sand content …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 20 Jan 2026
In this study, we aim to identify the most appropriate methods for spatial interpolation of seabed sand content …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 2 Mar 2026
In this study, we aim to identify the most appropriate methods for spatial interpolation of seabed sand content …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 7 Mar 2026
In this study, we aim to identify the most appropriate methods for spatial interpolation of seabed sand content …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 25 Mar 2026
In this study, we aim to identify the most appropriate methods for spatial interpolation of seabed sand content …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 20 Apr 2026
In this study, we aim to identify the most appropriate methods for spatial interpolation of seabed sand content …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 30 Apr 2026
In this study, we aim to identify the most appropriate methods for spatial interpolation of seabed sand content …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 11 Jan 2026
In this study, we aim to identify the most appropriate methods for spatial interpolation of seabed sand content …
- HTML