Update in advance of conference

Author: zacharyaanglin

1 - Simple linear regression in Keras.ipynb

@@ -7,6 +7,13 @@
     "## 1 - Simple regression model in TensorFlow 2.0"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "https://www.tensorflow.org/tutorials/keras/regression"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -364,7 +371,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -381,16 +388,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<seaborn.axisgrid.PairGrid at 0x133915e48>"
+       "<seaborn.axisgrid.PairGrid at 0x13cd809e8>"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -589,7 +596,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -606,7 +613,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -619,7 +626,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -640,7 +647,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -649,7 +656,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -677,9 +684,16 @@
     "model.summary()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Pass an example batch through the model."
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
@@ -692,19 +706,19 @@
     {
      "data": {
       "text/plain": [
-       "array([[ 0.4062208 ],\n",
-       "       [ 0.14854293],\n",
-       "       [-0.53726494],\n",
-       "       [ 0.4551225 ],\n",
-       "       [ 0.03993351],\n",
-       "       [ 0.10648736],\n",
-       "       [ 0.07059113],\n",
-       "       [ 0.3804471 ],\n",
-       "       [ 0.00926753],\n",
-       "       [ 0.2917318 ]], dtype=float32)"
+       "array([[ 0.00580749],\n",
+       "       [ 0.11364451],\n",
+       "       [-1.0010507 ],\n",
+       "       [-0.00943041],\n",
+       "       [ 0.17769842],\n",
+       "       [ 0.07948378],\n",
+       "       [ 0.22951826],\n",
+       "       [-0.01827377],\n",
+       "       [-0.08627713],\n",
+       "       [ 0.22824478]], dtype=float32)"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 40,
      "metadata": {},
      "output_type": "execute_result"
     }