diff --git a/Neural Networks and Deep Learning/Deep Neural Network - Application.ipynb b/Neural Networks and Deep Learning/Deep Neural Network - Application.ipynb
index 79add884..a73c27d2 100644
--- a/Neural Networks and Deep Learning/Deep Neural Network - Application.ipynb	
+++ b/Neural Networks and Deep Learning/Deep Neural Network - Application.ipynb	
@@ -8,7 +8,7 @@
     "\n",
     "When you finish this, you will have finished the last programming assignment of Week 4, and also the last programming assignment of this course! \n",
     "\n",
-    "You will use use the functions you'd implemented in the previous assignment to build a deep network, and apply it to cat vs non-cat classification. Hopefully, you will see an improvement in accuracy relative to your previous logistic regression implementation.  \n",
+    "You will use the functions you'd implemented in the previous assignment to build a deep network, and apply it to cat vs non-cat classification. Hopefully, you will see an improvement in accuracy relative to your previous logistic regression implementation.  \n",
     "\n",
     "**After this assignment you will be able to:**\n",
     "- Build and apply a deep neural network to supervised learning. \n",
@@ -39,9 +39,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import time\n",
@@ -83,9 +81,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "train_x_orig, train_y, test_x_orig, test_y, classes = load_data()"
@@ -101,9 +97,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -133,9 +127,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -180,9 +172,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -318,9 +308,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# GRADED FUNCTION: two_layer_model\n",
@@ -426,9 +414,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -513,9 +499,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -546,7 +530,6 @@
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -626,9 +609,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# GRADED FUNCTION: n_layer_model\n",
@@ -709,7 +690,6 @@
    "cell_type": "code",
    "execution_count": 13,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -788,7 +768,6 @@
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -823,9 +802,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -877,7 +854,6 @@
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -926,7 +902,6 @@
    "cell_type": "code",
    "execution_count": 17,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -995,7 +970,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.7.0"
   }
  },
  "nbformat": 4,