diff --git a/docs/Explore Algorithms/Hyperparameter Tuning/HyperOpt.ipynb b/docs/Explore Algorithms/Hyperparameter Tuning/HyperOpt.ipynb
index d582dd1952..f1da6d2048 100644
--- a/docs/Explore Algorithms/Hyperparameter Tuning/HyperOpt.ipynb	
+++ b/docs/Explore Algorithms/Hyperparameter Tuning/HyperOpt.ipynb	
@@ -149,7 +149,8 @@
     "import numpy as np\n",
     "import pandas as pd\n",
     "from sklearn.datasets import fetch_california_housing\n",
-    "import time"
+    "import time\n",
+    "import requests"
    ]
   },
   {
@@ -158,12 +159,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "try:\n",
-    "    california = fetch_california_housing()\n",
-    "except EOFError:\n",
-    "    print(\"Encountered EOFError while downloading, retrying once...\")\n",
-    "    time.sleep(5)\n",
-    "    california = fetch_california_housing()\n",
+    "with open(\"cal_housing_py3.pkz\", \"wb\") as f:\n",
+    "    f.write(\n",
+    "        requests.get(\n",
+    "            \"https://mmlspark.blob.core.windows.net/datasets/cal_housing_py3.pkz\"\n",
+    "        ).content\n",
+    "    )\n",
+    "\n",
+    "california = fetch_california_housing(data_home=\".\", download_if_missing=False)\n",
     "\n",
     "feature_cols = [\"f\" + str(i) for i in range(california.data.shape[1])]\n",
     "header = [\"target\"] + feature_cols\n",
diff --git a/docs/Explore Algorithms/Regression/Quickstart - Vowpal Wabbit and LightGBM.ipynb b/docs/Explore Algorithms/Regression/Quickstart - Vowpal Wabbit and LightGBM.ipynb
index 5d5068042e..11fb68d070 100644
--- a/docs/Explore Algorithms/Regression/Quickstart - Vowpal Wabbit and LightGBM.ipynb	
+++ b/docs/Explore Algorithms/Regression/Quickstart - Vowpal Wabbit and LightGBM.ipynb	
@@ -27,7 +27,8 @@
     "import pandas as pd\n",
     "from pyspark.ml.feature import VectorAssembler\n",
     "from pyspark.ml.regression import LinearRegression\n",
-    "from sklearn.datasets import fetch_california_housing"
+    "from sklearn.datasets import fetch_california_housing\n",
+    "import requests"
    ]
   },
   {
@@ -47,7 +48,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "california = fetch_california_housing()\n",
+    "with open(\"cal_housing_py3.pkz\", \"wb\") as f:\n",
+    "    f.write(\n",
+    "        requests.get(\n",
+    "            \"https://mmlspark.blob.core.windows.net/datasets/cal_housing_py3.pkz\"\n",
+    "        ).content\n",
+    "    )\n",
+    "\n",
+    "california = fetch_california_housing(data_home=\".\", download_if_missing=False)\n",
     "\n",
     "feature_cols = [\"f\" + str(i) for i in range(california.data.shape[1])]\n",
     "header = [\"target\"] + feature_cols\n",
diff --git a/docs/Explore Algorithms/Vowpal Wabbit/Quickstart - Classification, Quantile Regression, and Regression.ipynb b/docs/Explore Algorithms/Vowpal Wabbit/Quickstart - Classification, Quantile Regression, and Regression.ipynb
index d60d70fb97..2e606caa4f 100644
--- a/docs/Explore Algorithms/Vowpal Wabbit/Quickstart - Classification, Quantile Regression, and Regression.ipynb	
+++ b/docs/Explore Algorithms/Vowpal Wabbit/Quickstart - Classification, Quantile Regression, and Regression.ipynb	
@@ -384,7 +384,8 @@
     "from synapse.ml.vw import VowpalWabbitRegressor, VowpalWabbitFeaturizer\n",
     "import numpy as np\n",
     "import pandas as pd\n",
-    "from sklearn.datasets import fetch_california_housing"
+    "from sklearn.datasets import fetch_california_housing\n",
+    "import requests"
    ]
   },
   {
@@ -393,7 +394,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "california = fetch_california_housing()\n",
+    "with open(\"cal_housing_py3.pkz\", \"wb\") as f:\n",
+    "    f.write(\n",
+    "        requests.get(\n",
+    "            \"https://mmlspark.blob.core.windows.net/datasets/cal_housing_py3.pkz\"\n",
+    "        ).content\n",
+    "    )\n",
+    "\n",
+    "california = fetch_california_housing(data_home=\".\", download_if_missing=False)\n",
     "\n",
     "feature_cols = [\"f\" + str(i) for i in range(california.data.shape[1])]\n",
     "header = [\"target\"] + feature_cols\n",