diff --git a/samples/04_gis_analysts_data_scientists/automate_building_footprint_extraction_using_instance_segmentation.ipynb b/samples/04_gis_analysts_data_scientists/automate_building_footprint_extraction_using_instance_segmentation.ipynb
index c413afa13..4b678c6f4 100644
--- a/samples/04_gis_analysts_data_scientists/automate_building_footprint_extraction_using_instance_segmentation.ipynb
+++ b/samples/04_gis_analysts_data_scientists/automate_building_footprint_extraction_using_instance_segmentation.ipynb
@@ -374,7 +374,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "`arcgis.learn` provides the MaskRCNN model for instance segmentation tasks, which is based on a pretrained convnet, like ResNet that acts as the 'backbone'. More details about MaskRCNN can be found [here](https://github.com/Esri/arcgis-python-api/blob/master/guide/14-deep-learning/How_MaskRCNN_works.ipynb)."
+    "`arcgis.learn` provides the MaskRCNN model for instance segmentation tasks, which is based on a pretrained convnet, like ResNet that acts as the 'backbone'. More details about MaskRCNN can be found [here](https://github.com/Esri/arcgis-python-api/blob/master/guide/14-deep-learning/how_maskrcnn_works.ipynb)."
    ]
   },
   {
diff --git a/samples/04_gis_analysts_data_scientists/shipwrecks_detection_using_bathymetric_data.ipynb b/samples/04_gis_analysts_data_scientists/shipwrecks_detection_using_bathymetric_data.ipynb
index 71959955e..a2006a9b2 100644
--- a/samples/04_gis_analysts_data_scientists/shipwrecks_detection_using_bathymetric_data.ipynb
+++ b/samples/04_gis_analysts_data_scientists/shipwrecks_detection_using_bathymetric_data.ipynb
@@ -615,7 +615,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "`arcgis.learn` provides the `MaskRCNN` model for instance segmentation tasks, which is based on a pretrained convnet, like ResNet that acts as the 'backbone'. More details about `MaskRCNN` can be found [here](https://github.com/Esri/arcgis-python-api/blob/master/guide/14-deep-learning/How_MaskRCNN_works.ipynb)."
+    "`arcgis.learn` provides the `MaskRCNN` model for instance segmentation tasks, which is based on a pretrained convnet, like ResNet that acts as the 'backbone'. More details about `MaskRCNN` can be found [here](https://github.com/Esri/arcgis-python-api/blob/master/guide/14-deep-learning/how_maskrcnn_works.ipynb)."
    ]
   },
   {