updated decision tree tutorial

Author: dhavalsays

ML/9_decision_tree/9_decision_tree.ipynb

@@ -20,7 +20,7 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
-    "scrolled": true
+    "scrolled": false
    },
    "outputs": [
     {
@@ -583,7 +583,9 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
      "data": {
@@ -636,7 +638,7 @@
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {
-    "scrolled": true
+    "scrolled": false
    },
    "outputs": [
     {
@@ -682,6 +684,36 @@
    "source": [
     "model.predict([[2,1,1]])"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Exercise: Build decision tree model to predict survival based on certain parameters**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"titanic.jpg\" height=200 width=400/>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "CSV file is available to download at https://github.com/codebasics/py/blob/master/ML/9_decision_tree/Exercise/titanic.csv\n",
+    "\n",
+    "##### In this file using following columns build a model to predict if person would survive or not,\n",
+    "\n",
+    "1. Pclass\n",
+    "1. Sex\n",
+    "1. Age\n",
+    "1. Fare\n",
+    "\n",
+    "##### Calculate score of your model"
+   ]
   }
  ],
  "metadata": {

ML/9_decision_tree/Exercise/9_decision_tree_exercise.ipynb

@@ -554,7 +554,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,