update titles and add Google Colab link

section-3-structured-data-projects/end-to-end-heart-disease-classification.ipynb

@@ -1,5 +1,16 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a target=\"_blank\" href=\"https://colab.research.google.com/github/mrdbourke/zero-to-mastery-ml/blob/master/section-3-structured-data-projects/end-to-end-heart-disease-classification.ipynb\">\n",
+    "  <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
+    "</a>\n",
+    "\n",
+    "[View source code](https://github.com/mrdbourke/zero-to-mastery-ml/blob/master/section-3-structured-data-projects/end-to-end-heart-disease-classification.ipynb) | [Read notebook in online book format](https://dev.mrdbourke.com/zero-to-mastery-ml/end-to-end-heart-disease-classification/)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -3314,7 +3325,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Tune KNeighborsClassifier (K-Nearest Neighbors or KNN) by hand\n",
+    "### 6.1 Tune KNeighborsClassifier (K-Nearest Neighbors or KNN) by hand\n",
     "\n",
     "There are several hyperparameters we can tune for the K-Nearest Neighbors (KNN) algorithm (or [`sklearn.neighbors.KNeighborsClassifier`](https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html)).\n",
     "\n",
@@ -3475,7 +3486,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Tuning models with with [`RandomizedSearchCV`](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.RandomizedSearchCV.html)\n",
+    "### 6.2 Tuning models with with [`RandomizedSearchCV`](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.RandomizedSearchCV.html)\n",
     "\n",
     "Reading the Scikit-Learn documentation for [`LogisticRegression`](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegressionCV.html#sklearn.linear_model.LogisticRegressionCV), we find there's a number of different hyperparameters we can tune.\n",
     "\n",
@@ -3687,7 +3698,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Tuning a model with [`GridSearchCV`](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html)\n",
+    "### 6.3 Tuning a model with [`GridSearchCV`](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html)\n",
     "\n",
     "The difference between `RandomizedSearchCV` and `GridSearchCV` is: \n",
     "\n",
@@ -3787,7 +3798,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Evaluating a classification model, beyond accuracy\n",
+    "## 7. Evaluating a classification model, beyond accuracy\n",
     "\n",
     "Now we've got a tuned model, let's get some of the metrics we discussed before.\n",
     "\n",
@@ -3898,7 +3909,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### ROC Curve and AUC Scores\n",
+    "### 7.1 ROC Curve and AUC Scores\n",
     "\n",
     "What's a ROC curve?\n",
     "\n",
@@ -3962,7 +3973,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Creating a confusion matrix \n",
+    "### 7.2 Creating a confusion matrix \n",
     "\n",
     "A confusion matrix is a visual way to show where your model made the right predictions and where it made the wrong predictions (or in other words, got confused).\n",
     "\n",
@@ -4049,7 +4060,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Classification report\n",
+    "### 7.3 Classification report\n",
     "\n",
     "A classification report is a collection of different metrics and other details.\n",
     "\n",
@@ -4368,7 +4379,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Feature importance\n",
+    "## 8. Feature importance\n",
     "\n",
     "Feature importance is another way of asking, \"Which features contribute most to the outcomes of the model?\"\n",
     "\n",
@@ -4694,7 +4705,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 6. Experimentation\n",
+    "## 9. Experimentation\n",
     "\n",
     "We've completed all the metrics your boss requested!\n",
     "\n",
@@ -4725,7 +4736,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### What next?\n",
+    "## What next?\n",
     "\n",
     "You might be wondering, what happens when the evaluation metric doesn't get hit?\n",
     "\n",