diff --git a/1_TensorFlow_Basics/Tutorials/4_Save_and_Restore.ipynb b/1_TensorFlow_Basics/Tutorials/4_Save_and_Restore.ipynb
index a73215d..7f502df 100644
--- a/1_TensorFlow_Basics/Tutorials/4_Save_and_Restore.ipynb
+++ b/1_TensorFlow_Basics/Tutorials/4_Save_and_Restore.ipynb
@@ -56,6 +56,26 @@
     "```\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 0. Import the required libraries:\n",
+    "\n",
+    "We will start with importing the required Python libraries."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#imports\n",
+    "import tensorflow as tf\n",
+    "import os"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -67,13 +87,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 2,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "import tensorflow as tf\n",
     "# create variables a and b\n",
     "a = tf.get_variable(\"A\", initializer=tf.constant(3, shape=[2]))\n",
     "b = tf.get_variable(\"B\", initializer=tf.constant(5, shape=[3]))"
@@ -95,10 +112,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 3,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# initialize all of the variables\n",
@@ -114,7 +129,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -148,7 +163,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -180,7 +195,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -211,7 +226,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -219,13 +234,12 @@
      "output_type": "stream",
      "text": [
       "saved_variable.data-00000-of-00001\n",
-      "saved_variable.meta\n",
-      "saved_variable.index\n"
+      "saved_variable.index\n",
+      "saved_variable.meta\n"
      ]
     }
    ],
    "source": [
-    "import os\n",
     "for file in os.listdir('.'):\n",
     "    if 'saved_variable' in file:\n",
     "        print(file)"
@@ -252,7 +266,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -292,7 +306,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -336,7 +350,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -392,7 +406,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -446,7 +460,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -489,7 +503,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -554,10 +568,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 14,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# create saver object\n",
@@ -573,7 +585,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -581,7 +593,7 @@
      "output_type": "stream",
      "text": [
       "---------------------------------------------------------\n",
-      "Validation loss: 0.31, Validation accuracy: 91.7%\n",
+      "Validation loss: 0.32, Validation accuracy: 91.4%\n",
       "---------------------------------------------------------\n",
       "model saved in ./linear_model\n"
      ]
@@ -619,7 +631,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -627,8 +639,8 @@
      "output_type": "stream",
      "text": [
       "linear_model.data-00000-of-00001\n",
-      "linear_model.meta\n",
-      "linear_model.index\n"
+      "linear_model.index\n",
+      "linear_model.meta\n"
      ]
     }
    ],
@@ -647,7 +659,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -656,24 +668,24 @@
      "text": [
       "INFO:tensorflow:Restoring parameters from ./linear_model\n",
       "---------------------------------------------------------\n",
-      "Test loss: 0.32, test accuracy: 91.4%\n",
+      "Test loss: 0.32, test accuracy: 91.2%\n",
       "---------------------------------------------------------\n",
       "\n",
-      "W =  [[ 0.01166079  0.00214     0.01031407 ...  0.00138819 -0.00628771\n",
-      "   0.00202227]\n",
-      " [ 0.00583515 -0.0049552   0.00155843 ... -0.00023047 -0.00729254\n",
-      "  -0.00405982]\n",
-      " [ 0.01768233 -0.00875011 -0.01097609 ... -0.00147737 -0.00018261\n",
-      "  -0.00989295]\n",
+      "W =  [[-0.00795777  0.00179533 -0.01632378 ...  0.01127853 -0.0165657\n",
+      "  -0.01905626]\n",
+      " [-0.00036186 -0.01072511  0.01412622 ... -0.01868354  0.0091197\n",
+      "  -0.01899963]\n",
+      " [ 0.01169185  0.00378057 -0.00452419 ...  0.01239008  0.00784524\n",
+      "  -0.00559599]\n",
       " ...\n",
-      " [ 0.00241719  0.00672442 -0.00274725 ...  0.01378055 -0.00826664\n",
-      "  -0.00141329]\n",
-      " [-0.01537914 -0.00139711  0.0020227  ... -0.00358674  0.00436257\n",
-      "  -0.00737171]\n",
-      " [ 0.00428195  0.00458214 -0.01005485 ...  0.00464132  0.00323565\n",
-      "  -0.00285462]]\n",
-      "b =  [-0.14392368  0.2330784  -0.04319457 -0.10059926  0.06679667  0.21008638\n",
-      " -0.0314009   0.14653793 -0.30130398 -0.05041829]\n"
+      " [ 0.00589321 -0.01055128  0.00599118 ... -0.0021277   0.00593736\n",
+      "   0.00538401]\n",
+      " [ 0.0050825   0.00028797 -0.00596465 ... -0.00036289  0.00454178\n",
+      "  -0.00049127]\n",
+      " [-0.00797494 -0.00345959  0.002974   ...  0.01462011 -0.00961047\n",
+      "   0.00482459]]\n",
+      "b =  [-0.13907638  0.24205    -0.04328492 -0.09594144  0.0636861   0.19795758\n",
+      " -0.03274642  0.12884071 -0.2828767  -0.04605722]\n"
      ]
     }
    ],
@@ -683,7 +695,7 @@
     "# run the session\n",
     "with tf.Session() as sess:\n",
     "    # restore the saved vairable\n",
-    "    imported_graph.restore(sess, './linear_model')\n",
+    "    saver.restore(sess, './linear_model')\n",
     "    \n",
     "    # Accuracy\n",
     "    feed_dict_test = {x: data.test.images, y: data.test.labels}\n",
@@ -710,7 +722,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -923,7 +935,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -932,7 +944,7 @@
      "text": [
       "INFO:tensorflow:Restoring parameters from ./linear_model\n",
       "---------------------------------------------------------\n",
-      "Test loss: 0.32, test accuracy: 91.4%\n",
+      "Test loss: 0.32, test accuracy: 91.2%\n",
       "---------------------------------------------------------\n",
       "\n"
      ]
@@ -977,7 +989,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.4"
+   "version": "3.6.8"
   }
  },
  "nbformat": 4,