diff --git a/lab-guided-regression-models-with-keras.ipynb b/lab-guided-regression-models-with-keras.ipynb
index b3234ec..3e55554 100644
--- a/lab-guided-regression-models-with-keras.ipynb
+++ b/lab-guided-regression-models-with-keras.ipynb
@@ -855,16 +855,7 @@
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "2024-08-14 17:38:10.878028: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
-      "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from tensorflow import keras"
    ]
@@ -889,8 +880,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from keras.models import Sequential\n",
-    "from keras.layers import Dense"
+    "from tensorflow.keras.models import Sequential\n",
+    "from tensorflow.keras.layers import Dense"
    ]
   },
   {
@@ -972,16 +963,7 @@
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/joaorochaemelo/code/IH/venv_ironhack/lib/python3.11/site-packages/keras/src/layers/core/dense.py:87: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
-      "  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# build the model\n",
     "model = regression_model()"
@@ -1011,7 +993,19 @@
    "cell_type": "code",
    "execution_count": 15,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31mThe Kernel crashed while executing code in the current cell or a previous cell. \n",
+      "\u001b[1;31mPlease review the code in the cell(s) to identify a possible cause of the failure. \n",
+      "\u001b[1;31mClick <a href='https://aka.ms/vscodeJupyterKernelCrash'>here</a> for more info. \n",
+      "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
+     ]
+    }
+   ],
    "source": [
     "from sklearn.model_selection import train_test_split\n",
     "\n",
@@ -1030,224 +1024,7 @@
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Epoch 1/100\n",
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-      "Epoch 93/100\n",
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-      "Epoch 94/100\n",
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-      "Epoch 95/100\n",
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-      "Epoch 96/100\n",
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-      "Epoch 97/100\n",
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-      "Epoch 98/100\n",
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-      "Epoch 99/100\n",
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-      "Epoch 100/100\n",
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-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<keras.src.callbacks.history.History at 0x1411f6050>"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# fit the model\n",
     "model.fit(X_train, y_train, epochs=100, verbose=2)"
@@ -1268,7 +1045,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -1293,7 +1070,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -1365,7 +1142,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.8.15"
   }
  },
  "nbformat": 4,