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773 datasets for “machine-learning”

  1. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 5 Mar 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  2. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 16 Mar 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  3. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 29 Mar 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  4. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 4 Apr 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  5. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 10 Apr 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  6. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 16 Apr 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  7. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 5 May 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  8. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 5 Jun 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  9. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 17 Jun 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  10. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 23 Jun 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  11. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 27 Jun 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  12. Data.gov Catalog

    Closed-loop Autonomous Materials Exploration and Optimization 1.0

    National Institute of Standards and TechnologyUpdated 20 Aug 2020

    Code and demonstration data for the paper, "On-the-fly closed-loop materials discovery via Bayesian active learning …

    • X-ZIP-COMPRESSED
    • PLAIN
  13. Opendatasoft hubLive preview

    Data from paper entitled "Explainable machine learning to identify activity-related, insulin and dietary thresholds for prevention of exercise-associated hypoglycaemia and hyperglycaemia in free-living children with type 1 diabetes"

    IQBAL, AsifUpdated 18 Feb 2026

    … Ensemble machine-learning models predicted hypoglycaemia (<70 mg·dL⁻¹) and hyperglycaemia (>180 mg·dL⁻¹) during exercise …

    • CSV
    • JSON
    • GEOJSON
    • ODS API
  14. Opendatasoft hubLive preview

    1 Month-long skylight polarization images dataset

    POUGHON, LeoUpdated 14 Mar 2024

    Lien vers la fiche source A public database composed of real-world color polarimetric images of the sky …

    • CSV
    • JSON
    • GEOJSON
    • ODS API
  15. Data.gov Catalog

    Automated Fish Detection and Wildlife Tracking for Marine Energy Applications: Final Report and Review

    Booz Allen Hamilton Inc.Updated 17 Aug 2026

    … The project analyzes how modern computer-vision and machine-learning techniques can support reductions in manual labor, improve …

    • DOCX
  16. Data.gov Catalog

    Data from: Hyperspectral reflectance and machine learning for multi-site monitoring of cotton growth

    Agricultural Research ServiceUpdated 2 May 2025

    Two field research projects focused on cotton were conducted at the El Reno, OK and Temple, TX USDA …

    • CSV
  17. Data.gov Catalog

    AOML_ET: Partial pressure of CO2 (pCO2) and sea-air CO2 fluxes for the global ocean, along with the predictor variables from 1998-01-01 to 2023-12-30, using an Extra Trees (extremely randomized trees) machine learning (NCEI Accession 0298989)

    NOAA National Centers for Environmental InformationUpdated 21 Nov 2024

    … the extremely randomized trees or extra trees, ET machine learning approach. The products are labeled as AOML_ET …

    • HTML
    • VALUE
  18. Data.gov Catalog

    Mars surface image (Curiosity rover) labeled data set version 1

    NASAUpdated 23 Apr 2025

    This data set consists of 6691 images spanning 24 classes that were collected by the Mars Science Laboratory …

    • HTML
  19. Data.gov Catalog

    Executive Branch Artificial Intelligence System Inventory

    data.ct.govUpdated 8 Dec 2025

    … set of techniques, including, but not limited to, machine learning, that is designed to approximate a cognitive task.

    • JSON
    • XML
    • CSV
  20. Data.gov Catalog

    Machine learning model that estimates total monthly and annual per capita public-supply water use (version 2.0)

    U.S. Geological SurveyUpdated 27 Aug 2024

    This child item describes a machine learning model that was developed to estimate public-supply water use by …

    • XML
“machine-learning” datasets · Open Data Finder