Fix Jupyter Notebook Headers

examples/models/aws_eks_deep_mnist/aws_eks_deep_mnist.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Tensorflow MNIST Model\n",
+    "# AWS Elastic Kubernetes Service (EKS) Deep MNIST\n",
     "In this example we will deploy a tensorflow MNIST model in Amazon Web Services' Elastic Kubernetes Service (EKS).\n",
     "\n",
     "This tutorial will break down in the following sections:\n",
@@ -25,20 +25,22 @@
     "\n",
     "#### Let's get started! 🚀🔥\n",
     "\n",
-    "# Dependencies:\n",
+    "## Dependencies:\n",
     "\n",
-    "* Docker\n",
-    "* Helm\n",
-    "* Kubectl\n",
-    "* EKS CLI\n",
-    "* AWS Cli\n"
+    "* Helm v2.13.1+\n",
+    "* A Kubernetes cluster running v1.13 or above (minkube / docker-for-windows work well if enough RAM)\n",
+    "* kubectl v1.14+\n",
+    "* EKS CLI v0.1.32\n",
+    "* AWS Cli v1.16.163\n",
+    "* Python 3.6+\n",
+    "* Python DEV requirements\n"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 1) Train a tensorflow model to predict mnist locally\n",
+    "## 1) Train a tensorflow model to predict mnist locally\n",
     "We will load the mnist images, together with their labels, and then train a tensorflow model to predict the right labels"
    ]
   },
@@ -101,7 +103,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 2) Containerise the tensorflow model with our docker utility"
+    "## 2) Containerise the tensorflow model with our docker utility"
    ]
   },
   {
@@ -187,7 +189,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 3) Send some data to the docker model to test it\n",
+    "## 3) Send some data to the docker model to test it\n",
     "We first run the docker image we just created as a container called \"mnist_predictor\""
    ]
   },
@@ -317,7 +319,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 4) Install and configure AWS tools to interact with AWS"
+    "## 4) Install and configure AWS tools to interact with AWS"
    ]
   },
   {
@@ -445,7 +447,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 5) Use the AWS tools to create and setup EKS cluster with Seldon\n",
+    "## 5) Use the AWS tools to create and setup EKS cluster with Seldon\n",
     "In this example we will create a cluster with 2 nodes, with a minimum of 1 and a max of 3. You can tweak this accordingly.\n",
     "\n",
     "If you want to check the status of the deployment you can go to AWS CloudFormation or to the EKS dashboard.\n",
@@ -538,7 +540,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Install Seldon Core"
+    "## Install Seldon Core"
    ]
   },
   {
@@ -858,7 +860,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Push docker image\n",
+    "## Push docker image\n",
     "In order for the EKS seldon deployment to access the image we just built, we need to push it to the Elastic Container Registry (ECR).\n",
     "\n",
     "If you have any issues please follow the official AWS documentation: https://docs.aws.amazon.com/AmazonECR/latest/userguide/docker-basics.html"
@@ -1034,7 +1036,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Running the Model\n",
+    "## Running the Model\n",
     "We will now run the model.\n",
     "\n",
     "Let's first have a look at the file we'll be using to trigger the model:"
@@ -1197,7 +1199,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Test the model\n",
+    "## Test the model\n",
     "Now we can test the model, let's first find out what is the URL that we'll have to use:"
    ]
   },