diff --git a/tutorial_regression_data.ipynb b/tutorial_regression_data.ipynb
index 981e223e2c5925a975da44b5ce2fd3d995880112..e85fa504bdea8ba8103914f0c08eb1cf47cc6fb8 100644
--- a/tutorial_regression_data.ipynb
+++ b/tutorial_regression_data.ipynb
@@ -51,7 +51,8 @@
    "execution_count": 12,
    "outputs": [],
    "source": [
-    "(trainX,trainX_img, trainY, testX,testX_img,testY), normalizer = load_house_dataset_data(test_size=0.2,random_state=666)\n",
+    "dataset_path = '/content/pilula_deep_learning/HousesDataset/Houses Dataset'\n",
+    "(trainX,trainX_img, trainY, testX,testX_img,testY), normalizer = load_house_dataset_data(test_size=0.2,random_state=666,path=dataset_path)\n",
     "input_shape = trainX.shape[1]\n"
    ],
    "metadata": {
diff --git a/tutorial_regression_data_image.ipynb b/tutorial_regression_data_image.ipynb
index d0c75d59e0689b8bbd3f177975802253cb943e3d..f1611745046be424c0c1ada886da6ff29988332c 100644
--- a/tutorial_regression_data_image.ipynb
+++ b/tutorial_regression_data_image.ipynb
@@ -50,7 +50,8 @@
    "execution_count": 12,
    "outputs": [],
    "source": [
-    "(trainX_data,trainX_img, trainY, testX_data,testX_img,testY), normalizer = load_house_dataset_data(test_size=0.2,random_state=666,type=DatasetType.Both)\n",
+    "dataset_path = '/content/pilula_deep_learning/HousesDataset/Houses Dataset'\n",
+    "(trainX_data,trainX_img, trainY, testX_data,testX_img,testY), normalizer = load_house_dataset_data(test_size=0.2,random_state=666,type=DatasetType.Both,path=dataset_path)\n",
     "trainX = [trainX_data,trainX_img['bathroom_img']]\n",
     "testX = [testX_data,testX_img['bathroom_img']]\n",
     "input_shape_data = trainX[0].shape[1]\n",
diff --git a/tutorial_regression_image_finetune.ipynb b/tutorial_regression_image_finetune.ipynb
index 9d207bc771b1476a965489edb89aa100d9fdadaf..2e05b8c733422b6adcebd7bebbf2ff09d517b20a 100644
--- a/tutorial_regression_image_finetune.ipynb
+++ b/tutorial_regression_image_finetune.ipynb
@@ -264,7 +264,8 @@
     }
    ],
    "source": [
-    "(trainX_data,trainX_img, trainY, testX_data,testX_img,testY), normalizer = load_house_dataset_data(test_size=0.2,random_state=666,type=DatasetType.Both)\n",
+    "dataset_path = '/content/pilula_deep_learning/HousesDataset/Houses Dataset'\n",
+    "(trainX_data,trainX_img, trainY, testX_data,testX_img,testY), normalizer = load_house_dataset_data(test_size=0.2,random_state=666,type=DatasetType.Both,path=dataset_path)\n",
     "trainX = trainX_img['bathroom_img']\n",
     "testX = testX_img['bathroom_img']\n",
     "input_shape = trainX.shape[1]\n",
diff --git a/tutorial_regression_image_scratch.ipynb b/tutorial_regression_image_scratch.ipynb
index 2cd79930ae9783001c912f7917b5c750e49d964f..0e5863c944782008df685f9c05fa149add0ee983 100644
--- a/tutorial_regression_image_scratch.ipynb
+++ b/tutorial_regression_image_scratch.ipynb
@@ -283,7 +283,8 @@
     }
    ],
    "source": [
-    "(trainX_data,trainX_img, trainY, testX_data,testX_img,testY), normalizer = load_house_dataset_data(test_size=0.2,random_state=666,type=DatasetType.Both)\n",
+    "dataset_path = '/content/pilula_deep_learning/HousesDataset/Houses Dataset'\n",
+    "(trainX_data,trainX_img, trainY, testX_data,testX_img,testY), normalizer = load_house_dataset_data(test_size=0.2,random_state=666,type=DatasetType.Both,path=dataset_path)\n",
     "trainX = trainX_img['frontal_img']\n",
     "testX = testX_img['frontal_img']\n",
     "input_shape = trainX.shape[1]\n",