add nb for detreg

Author: priyankatuteja

samples/04_gis_analysts_data_scientists/detecting_palm_trees_using_deep_learning.ipynb

@@ -1284,15 +1284,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 24,
    "id": "33d93f03",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Computing model metrics...\n"
+      "Computing model metrics...\n",
+      "Published DLPK Item Id: 9406080ccb6b499b9e2651c7b36f969d\n"
      ]
     },
     {
@@ -1301,13 +1302,13 @@
        "WindowsPath('C:/Users/pri10421/AppData/Local/Temp/detecting_palm_trees_using_deep_learning/models/palm_e100')"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "detreg_model.save('palm_e100')"
+    "detreg_model.save('palm_e100', publish=True)"
    ]
   },
   {
@@ -1323,7 +1324,7 @@
    "id": "27b740d8",
    "metadata": {},
    "source": [
-    "The bulk of the work in extracting features from imagery is preparing the data, creating training samples, and training the model. Now that these steps have been completed, we'll use the [trained model]() to detect palm trees throughout your imagery. Object detection is a process that typically requires multiple tests to achieve the best results. There are several parameters that you can alter to allow your model to perform best. To test these parameters quickly, we'll try detecting trees in a small section of the image. Once you're satisfied with the results, we'll extend the detection tools to the full image."
+    "The bulk of the work in extracting features from imagery is preparing the data, creating training samples, and training the model. Now that these steps have been completed, we'll use the [trained model](https://www.arcgis.com/home/item.html?id=9406080ccb6b499b9e2651c7b36f969d) to detect palm trees in the desired imagery. Object detection is a process that typically requires multiple tests to achieve the best results. There are several parameters that you can alter to allow your model to perform best. To test these parameters quickly, we'll try detecting trees in a small section of the image. Once you're satisfied with the results, we'll extend the detection tools to the full image."
    ]
   },
   {