02 - Get AutoML Prediction.ipynb

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        "# Get Diabetes Prediction from Automated ML Endpoint\r\n",
        "\r\n",
        "Modify the code in the cell below to use the ***ENDPOINT*** and ***PRIMARY_KEY*** for your **auto-predict-diabetes** service. Then run the cell to submit new patient data and retrieve the predicted classifications. "
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        "endpoint = 'ENDPOINT' #Replace with your endpoint\r\n",
        "key = 'PRIMARY_KEY' #Replace with your key\r\n",
        "\r\n",
        "import json\r\n",
        "import requests\r\n",
        "\r\n",
        "#Features for a patient\r\n",
        "x = [{\"PatientID\": 1,\r\n",
        "      \"Pregnancies\": 5,\r\n",
        "      \"PlasmaGlucose\": 181.0,\r\n",
        "      \"DiastolicBloodPressure\": 90.6,\r\n",
        "      \"TricepsThickness\": 34.0,\r\n",
        "      \"SerumInsulin\": 23.0,\r\n",
        "      \"BMI\": 43.51,\r\n",
        "      \"DiabetesPedigree\": 1.21,\r\n",
        "      \"Age\": 21.0}]\r\n",
        "\r\n",
        "#Create a \"data\" JSON object\r\n",
        "input_json = json.dumps({\"data\": x})\r\n",
        "\r\n",
        "#Set the content type and authentication for the request\r\n",
        "headers = {\"Content-Type\":\"application/json\",\r\n",
        "           \"Authorization\":\"Bearer \" + key}\r\n",
        "\r\n",
        "#Send the request\r\n",
        "response = requests.post(endpoint, input_json, headers=headers)\r\n",
        "\r\n",
        "#If we got a valid response, display the predictions\r\n",
        "if response.status_code == 200:\r\n",
        "    y = json.loads(response.json())\r\n",
        "    #Get the first prediction in the results\r\n",
        "    print(\"Prediction:\", y[\"result\"][0])\r\n",
        "    if y[\"result\"][0] == 1:\r\n",
        "        print('Diabetic')\r\n",
        "    else:\r\n",
        "        print(\"Not Diabetic\")\r\n",
        "else:\r\n",
        "    print(response)"
      ],
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