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773 datasets for “machine-learning”
- Data.gov Catalog
Tri-axial acceleration data from California condors (Gymnogyps californianus), California, USA
U.S. Geological SurveyUpdated 6 Sept 2024
We outfitted nine condors in a flight pen with patagial tags, each with a unique ID, and a …
- XML
- Opendatasoft hubLive preview
Deep-learning-ready RGB-Depth imaging dataset of early-growth plants.
MERCIER FélixUpdated 16 Dec 2024
Lien vers la fiche source Dataset composed of RGB, Depth, and Infrared images acquired while monitoring the growth …
- 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.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
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 23 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
Australian Ocean Data NetworkUpdated 12 Feb 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 5 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
Australian Ocean Data NetworkUpdated 16 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
Australian Ocean Data NetworkUpdated 29 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
Australian Ocean Data NetworkUpdated 4 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 10 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 16 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 28 Apr 2026
In this study, we aim to identify the most appropriate methods for spatial interpolation of seabed sand content …
- HTML