Update start docs description to correctly say using the fraud dataset (

#2370)

* init

* release notes

docs/source/release_notes.rst

@@ -7,6 +7,7 @@ Release Notes
         * Added ``thresholding_objective`` argument to ``AutoMLSearch`` for binary classification problems :pr:`2320`
     * Changes
     * Documentation Changes
+        * Fixed start page code and description dataset naming discrepancy :pr:`2370`
     * Testing Changes
         * Add ``pytest-timeout``. All tests that run longer than 6 minutes will fail. :pr:`2374`
         * Separated the dask tests out into separate github action jobs to isolate dask failures. :pr:`2376`

docs/source/start.ipynb

@@ -11,7 +11,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "In this guide, we'll show how you can use EvalML to automatically find the best pipeline for predicting whether a patient has breast cancer. Along the way, we'll highlight EvalML's built-in tools and features for understanding and interacting with the search process."
+    "In this guide, we'll show how you can use EvalML to automatically find the best pipeline for predicting whether or not a credit card transaction is fradulent. Along the way, we'll highlight EvalML's built-in tools and features for understanding and interacting with the search process."
    ]
   },
   {