Skip to content

Added new samples to items_metadata #1257

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
achapkowski merged 1 commit into from
May 25, 2022
Merged

Added new samples to items_metadata #1257

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
54 changes: 54 additions & 0 deletions items_metadata.yaml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -906,6 +906,60 @@ samples:
# licenseInfo: ""
# runtime: advanced
# tags: ["Data Science", "GIS", "Site Suitability", "Raster Analysis"]
# - title: Lunar Craters Detection using Deep Learning
# url: https://www.arcgis.com/home/item.html?id=a1406e406ec746f4b33fcf0aba55e980
# path: ./samples/04_gis_analysts_data_scientists/lunar_craters_detection_from_dem_using_deep_learning.ipynb
# thumbnail: ./static/thumbnails/default.png
# snippet: This notebook will demonstrate how the ArcGIS API for Python can be used to train a deep learning crater detection model using a Digital Elevation Model (DEM), which can then be deployed in ArcGIS Pro or ArcGIS Enterprise.
# description: This notebook will demonstrate how the ArcGIS API for Python can be used to train a deep learning crater detection model using a Digital Elevation Model (DEM), which can then be deployed in ArcGIS Pro or ArcGIS Enterprise.
# licenseInfo: ""
# runtime: advanced
# tags: ["Data Science", "GIS", "Raster Analysis"]
# - title: Training a wind turbine detection model using large volumes of training data
# url: https://www.arcgis.com/home/item.html?id=d127b9f7cfb54283bec551d9e9911b33
# path: ./samples/04_gis_analysts_data_scientists/training_a_wind_turbine_detection_model_using_large_volume_of_training_data.ipynb
# thumbnail: ./static/thumbnails/default.png
# snippet: This notebook trains a wind turbine detection model using large volumes of training data.
# description: This notebook trains a wind turbine detection model using large volumes of training data.
# licenseInfo: ""
# runtime: advanced
# tags: ["Data Science", "GIS", "Raster Analysis"]
# - title: Landsat 8 to Sentinel-2 using Pix2Pix
# url: https://www.arcgis.com/home/item.html?id=3576325e2d4c4dbfa56a4217882134f9
# path: ./samples/04_gis_analysts_data_scientists/landsat8_to_sentinel2_pix2pix.ipynb
# thumbnail: ./static/thumbnails/default.png
# snippet: In this notebook, we use the Pix2Pix model to convert 30 meter resolution Landsat 8 imagery to 10 meter resolution Sentinel-2 imagery.
# description: In this notebook, we use the Pix2Pix model to convert 30 meter resolution Landsat 8 imagery to 10 meter resolution Sentinel-2 imagery.
# licenseInfo: ""
# runtime: advanced
# tags: ["Data Science", "GIS", "Raster Analysis"]
# - title: Image scene classification using FeatureClassifier
# url: https://www.arcgis.com/home/item.html?id=6ea5821a4a864b3990bb13ea1c77887f
# path: ./samples/04_gis_analysts_data_scientists/image_scene_classification_using_feature_classifier.ipynb
# thumbnail: ./static/thumbnails/default.png
# snippet: In this notebook, we will train an object classification model on image data from an external source and use that model for inferencing in ArcGIS Pro.
# description: In this notebook, we will train an object classification model on image data from an external source and use that model for inferencing in ArcGIS Pro.
# licenseInfo: ""
# runtime: advanced
# tags: ["Data Science", "GIS", "Raster Analysis"]
# - title: Covid case forecasting Using TimeSeriesModel from arcgis.learn
# url: https://www.arcgis.com/home/item.html?id=b0748b483e104389b6ac51dbacb48e8a
# path: ./samples/04_gis_analysts_data_scientists/covid_case_forecasting_for_alabama_state_using_timeseriesmodel_from_arcgis_learn.ipynb
# thumbnail: ./static/thumbnails/default.png
# snippet: This notebook uses the deep learning TimeSeriesModel from arcgis.learn to analyze confirmed cases for all counties in Alabama.
# description: This notebook uses the deep learning TimeSeriesModel from arcgis.learn to analyze confirmed cases for all counties in Alabama.
# licenseInfo: ""
# runtime: advanced
# tags: ["Data Science", "GIS", "Raster Analysis"]
# - title: Image Captioning Using Deep Learning
# url: https://www.arcgis.com/home/item.html?id=e43047eb5ae7407ab651a1324e1ba529
# path: ./samples/04_gis_analysts_data_scientists/image_captioning_using_deep_learning.ipynb
# thumbnail: ./static/thumbnails/default.png
# snippet: This sample shows how ArcGIS API for Python can be used to train ImageCaptioner model using Remote Sensing Image Captioning Dataset.
# description: This sample shows how ArcGIS API for Python can be used to train ImageCaptioner model using Remote Sensing Image Captioning Dataset.
# licenseInfo: ""
# runtime: advanced
# tags: ["Data Science", "GIS", "Raster Analysis"]

guides: []
labs:
Expand Down