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AtmaMani merged 1 commit into from
Oct 1, 2021
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Update items_metadata.yaml #1106

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28 changes: 28 additions & 0 deletions items_metadata.yaml
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Expand Up @@ -852,6 +852,34 @@ samples:
# licenseInfo: ""
# runtime: advanced
# tags: ["Data Science", "GIS", "Site Suitability", "Raster Analysis"]
# - title: Coastline classification using Feature Classifier
# url: https://www.arcgis.com/home/item.html?id=9ef3ab6a0bde44e5bcbe68b165b8e6dd
# path: ./samples/04_gis_analysts_data_scientists/coastline_classification_using_feature_classifier.ipynb
# thumbnail: ./static/thumbnails/default.png
# snippet: In this sample notebook, we will see how we can classify these coastlines in the categories mentioned in figure 1, by training a Feature Classifier model.
# description: In this sample notebook, we will see how we can classify these coastlines in the categories mentioned in figure 1, by training a Feature Classifier model.
# licenseInfo: ""
# runtime: advanced
# tags: ["Data Science", "GIS", "Site Suitability", "Raster Analysis"]
# - title: Wildlife Species Identification in Camera Trap Images
# url: https://www.arcgis.com/home/item.html?id=aa06b3add8e143e08014a9a7a5d2c94b
# path: ./samples/04_gis_analysts_data_scientists/wildlife_species_identification_in_camera_trap_images.ipynb
# thumbnail: ./static/thumbnails/default.png
# snippet: This notebook will showcase a workflow to classify animal species in camera trap images.
# description: This notebook will showcase a workflow to classify animal species in camera trap images.
# licenseInfo: ""
# runtime: advanced
# tags: ["Data Science", "GIS", "Site Suitability", "Raster Analysis"]
# - title: Detecting deforestation in the Amazon rainforest using unsupervised K-means clustering on satellite imagery
# url: https://www.arcgis.com/home/item.html?id=cd3d2c1b7f4047f98bf07beb10ee2016
# path: ./samples/04_gis_analysts_data_scientists/detecting-deforestation-using-kmeans-clustering-on-sentinel-imagery.ipynb
# thumbnail: ./static/thumbnails/default.png
# snippet: This notebook will allow us to detect deforested areas in the Brazilian Amazon rainforest, using satellite imagery.
# description: This notebook will allow us to detect deforested areas in the Brazilian Amazon rainforest, using satellite imagery.
# licenseInfo: ""
# runtime: advanced
# tags: ["Data Science", "GIS", "Site Suitability", "Raster Analysis"]

guides: []
labs:
- title: Create Data
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