Updated ReadMe.md

Code/AMLNotebooks/CreateTrainingPipeline.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "3a71c651",
    "metadata": {},
    "outputs": [],
@@ -16,43 +16,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "ab074296",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Uploading an estimated of 7 files\n",
-      "Uploading ./data/Customer.csv\n",
-      "Uploaded ./data/Customer.csv, 1 files out of an estimated total of 7\n",
-      "Uploading ./data/residents_source1.csv\n",
-      "Uploaded ./data/residents_source1.csv, 2 files out of an estimated total of 7\n",
-      "Uploading ./data/residents_source2.csv\n",
-      "Uploaded ./data/residents_source2.csv, 3 files out of an estimated total of 7\n",
-      "Uploading ./data/payments.csv\n",
-      "Uploaded ./data/payments.csv, 4 files out of an estimated total of 7\n",
-      "Uploading ./data/surveys.csv\n",
-      "Uploaded ./data/surveys.csv, 5 files out of an estimated total of 7\n",
-      "Uploading ./data/leases.csv\n",
-      "Uploaded ./data/leases.csv, 6 files out of an estimated total of 7\n",
-      "Uploading ./data/workorders.csv\n",
-      "Uploaded ./data/workorders.csv, 7 files out of an estimated total of 7\n",
-      "Uploaded 7 files\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "$AZUREML_DATAREFERENCE_00e69dcf1f8540929c62cd32383b38f6"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Get the default datastore\n",
     "default_ds = ws.get_default_datastore()\n",
@@ -66,7 +33,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "f3323dac",
    "metadata": {},
    "outputs": [],
@@ -78,7 +45,7 @@
     "    'surveytype': DataType.to_string(),\n",
     "    'surverydate': DataType.to_datetime(),\n",
     "    'question': DataType.to_string(),\n",
-    "    'answer': DataType.to_long(),\n",
+    "    'answer': DataType.to_float(),\n",
     "    'FirstName': DataType.to_string(),\n",
     "    'LastName': DataType.to_string(),\n",
     "    'Name': DataType.to_string(),\n",

Deployment/AzureSetup.md

@@ -120,7 +120,7 @@ In order to perform the necessary actions in Customer Insights, you will need to
 
 # Step 6: Set Up AML Pipeline
 1. Launch the Azure Machine Learning studio [AML Studio](https://ml.azure.com/)
-2. Go to the `Notebooks` tab in the AML Studio and upload the folder `AML Notebooks` folder and `Data` folder
+2. Go to the `Notebooks` tab in the AML Studio and upload the `AML Notebooks` folder
 3. Go to the `Compute` tab in the AML Studio and click on the `Compute Instances` 
 4. Click `New` and create a new compute instance
 5. Click `Jupyter` and launch the compute instance