üpdated

Author: priyankatuteja

samples/04_gis_analysts_data_scientists/forecasting_pm2.5_using_big_data_analysis.ipynb

@@ -25,9 +25,9 @@
     "* [Uncover patterns in data](#Uncover-patterns-in-data)\n",
     "    * [Describe data](#Describe-data)\n",
     "    * [Commonly used methods of measurement](#Commonly-used-methods-of-measurement)\n",
-    "    * [Average PM 2.5 value by County](#Average-PM-2.5-value-by-County)\n",
+    "    * [Average PM 2.5 value by county](#Average-PM-2.5-value-by-county)\n",
     "* [Prepare time series data](#Prepare-time-series-data)   \n",
-    "* [Predict PM2.5](#Predict-PM25)\n",
+    "* [Predict PM2.5 using Facebook's Prophet model](#Predict-PM2.5-using-Facebook's-Prophet-model)\n",
     "* [Visualize result on Dashboard](#Visualize-result-on-Dashboard)\n",
     "* [Conclusion](#Conclusion)\n",
     "* [References](#References)"
@@ -1354,7 +1354,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Average PM 2.5 value by County"
+    "### Average PM 2.5 value by county"
    ]
   },
   {
@@ -1847,6 +1847,13 @@
     "series_data.query(as_df=True)[:5]"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Predict PM2.5 using Facebook's Prophet model"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},