Merge pull request #1257 from mohi9282/release_201_updates

Added new samples to items_metadata

Author: achapkowski

items_metadata.yaml

@@ -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: