diff --git a/ml1/2_5_2_Decision_Tree_Model.ipynb b/ml1/2_5_2_Decision_Tree_Model.ipynb
index f0a0f6d..932f9fb 100644
--- a/ml1/2_5_2_Decision_Tree_Model.ipynb
+++ b/ml1/2_5_2_Decision_Tree_Model.ipynb
@@ -74,7 +74,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -124,9 +124,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "DecisionTreeClassifier(max_depth=3, random_state=1)"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "from sklearn.tree import DecisionTreeClassifier\n",
     "import numpy as np\n",
@@ -145,9 +156,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Prediction  [1 0 1 1 1 0 0 1 0 2 0 0 1 2 0 1 2 2 1 1 0 0 2 0 0 2 1 1 2 2 2 2 0 0 1 1 0\n",
+      " 1 2 1 2 0 2 0 1 0 2 1 0 2 2 0 0 2 0 0 0 2 2 0 1 0 1 0 1 1 1 1 1 0 1 0 1 2\n",
+      " 0 0 0 0 2 2 0 1 1 2 1 0 0 2 1 1 0 1 1 0 2 1 2 1 2 0 1 0 0 0 2 1 2 1 2 1 2\n",
+      " 0]\n",
+      "Expected  [1 0 1 1 1 0 0 1 0 2 0 0 1 2 0 1 2 2 1 1 0 0 2 0 0 2 1 1 2 2 2 2 0 0 1 1 0\n",
+      " 1 2 1 2 0 2 0 1 0 2 1 0 2 2 0 0 2 0 0 0 2 2 0 1 0 1 0 1 1 1 1 1 0 1 0 1 2\n",
+      " 0 0 0 0 2 2 0 1 1 2 1 0 0 1 1 1 0 1 1 0 2 2 2 1 2 0 1 0 0 0 2 1 2 1 2 1 2\n",
+      " 0]\n"
+     ]
+    }
+   ],
    "source": [
     "print(\"Prediction \", model.predict(x_train))\n",
     "print(\"Expected \", y_train)"
@@ -162,9 +188,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Predicted probabilities [[0.         0.97368421 0.02631579]\n",
+      " [1.         0.         0.        ]\n",
+      " [0.         0.97368421 0.02631579]\n",
+      " [0.         0.97368421 0.02631579]\n",
+      " [0.         0.97368421 0.02631579]\n",
+      " [1.         0.         0.        ]\n",
+      " [1.         0.         0.        ]\n",
+      " [0.         0.97368421 0.02631579]\n",
+      " [1.         0.         0.        ]\n",
+      " [0.         0.         1.        ]]\n"
+     ]
+    }
+   ],
    "source": [
     "# Print the \n",
     "print(\"Predicted probabilities\", model.predict_proba(x_train[:10]))"
@@ -172,9 +215,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy in training 0.9821428571428571\n"
+     ]
+    }
+   ],
    "source": [
     "# Evaluate Accuracy in training\n",
     "\n",
@@ -185,9 +236,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy in testing  0.9210526315789473\n"
+     ]
+    }
+   ],
    "source": [
     "# Now we evaluate error in testing\n",
     "y_test_pred = model.predict(x_test)\n",
@@ -209,9 +268,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "InvocationException",
+     "evalue": "GraphViz's executables not found",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mInvocationException\u001b[0m                       Traceback (most recent call last)",
+      "\u001b[0;32m/tmp/ipykernel_47326/3723147494.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[0mgraph\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpydot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgraph_from_dot_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdot_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetvalue\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m \u001b[0mgraph\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite_png\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'iris-tree.png'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     15\u001b[0m \u001b[0mImage\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgraph\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcreate_png\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/anaconda3/lib/python3.8/site-packages/pydotplus/graphviz.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(path, f, prog)\u001b[0m\n\u001b[1;32m   1808\u001b[0m                 \u001b[0;32mlambda\u001b[0m \u001b[0mpath\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1809\u001b[0m                 \u001b[0mf\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfrmt\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1810\u001b[0;31m                 \u001b[0mprog\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprog\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mformat\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprog\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprog\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1811\u001b[0m             )\n\u001b[1;32m   1812\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/anaconda3/lib/python3.8/site-packages/pydotplus/graphviz.py\u001b[0m in \u001b[0;36mwrite\u001b[0;34m(self, path, prog, format)\u001b[0m\n\u001b[1;32m   1916\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1917\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1918\u001b[0;31m                 \u001b[0mfobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcreate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprog\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mformat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1919\u001b[0m         \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1920\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/anaconda3/lib/python3.8/site-packages/pydotplus/graphviz.py\u001b[0m in \u001b[0;36mcreate\u001b[0;34m(self, prog, format)\u001b[0m\n\u001b[1;32m   1957\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprogs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfind_graphviz\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1958\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprogs\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1959\u001b[0;31m                 raise InvocationException(\n\u001b[0m\u001b[1;32m   1960\u001b[0m                     'GraphViz\\'s executables not found')\n\u001b[1;32m   1961\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mInvocationException\u001b[0m: GraphViz's executables not found"
+     ]
+    }
+   ],
    "source": [
     "from IPython.display import Image \n",
     "from six import StringIO\n",
diff --git a/ml1/2_6_Model_Tuning.ipynb b/ml1/2_6_Model_Tuning.ipynb
index 228d7c8..df94314 100644
--- a/ml1/2_6_Model_Tuning.ipynb
+++ b/ml1/2_6_Model_Tuning.ipynb
@@ -517,9 +517,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "* [Plot the decision surface of a decision tree on the iris dataset](http://scikit-learn.org/stable/auto_examples/tree/plot_iris.html)\n",
-    "* [Learning scikit-learn: Machine Learning in Python](http://proquest.safaribooksonline.com/book/programming/python/9781783281930/1dot-machine-learning-a-gentle-introduction/ch01s02_html), Raúl Garreta; Guillermo Moncecchi, Packt Publishing, 2013.\n",
-    "* [Python Machine Learning](http://proquest.safaribooksonline.com/book/programming/python/9781783555130), Sebastian Raschka, Packt Publishing, 2015.\n",
+    "* [Plot the decision surface of a decision tree on the iris dataset](https://scikit-learn.org/stable/auto_examples/tree/plot_iris_dtc.html)\n",
+    "* [scikit-learn : Machine Learning Simplified](https://learning.oreilly.com/library/view/scikit-learn-machine/9781788833479/), Raúl Garreta; Guillermo Moncecchi, Packt Publishing, 2017.\n",
+    "* [Python Machine Learning](https://learning.oreilly.com/library/view/python-machine-learning/9781789955750/), Sebastian Raschka, Packt Publishing, 2019.\n",
     "* [Parameter estimation using grid search with cross-validation](http://scikit-learn.org/stable/auto_examples/model_selection/grid_search_digits.html)\n",
     "* [Decision trees in python with scikit-learn and pandas](http://chrisstrelioff.ws/sandbox/2015/06/08/decision_trees_in_python_with_scikit_learn_and_pandas.html)"
    ]
@@ -543,7 +543,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -557,7 +557,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.6"
+   "version": "3.8.12"
   },
   "latex_envs": {
    "LaTeX_envs_menu_present": true,