diff --git a/open-machine-learning-jupyter-book/ml-advanced/ensemble-learning/getting-started-with-ensemble-learning.ipynb b/open-machine-learning-jupyter-book/ml-advanced/ensemble-learning/getting-started-with-ensemble-learning.ipynb
index a3c7fd871..aff0f3d31 100644
--- a/open-machine-learning-jupyter-book/ml-advanced/ensemble-learning/getting-started-with-ensemble-learning.ipynb
+++ b/open-machine-learning-jupyter-book/ml-advanced/ensemble-learning/getting-started-with-ensemble-learning.ipynb
@@ -92,7 +92,7 @@
     "Let's look at another example of ensembles: an observation known as [Wisdom of the crowd](https://en.wikipedia.org/wiki/Wisdom_of_the_crowd). <img src=\"https://habrastorage.org/webt/zg/hw/b7/zghwb7oztkmv840odqkjpink1vw.png\" align=\"right\" width=15% height=15%> In 1906, [Francis Galton](https://en.wikipedia.org/wiki/Francis_Galton) visited a country fair in Plymouth where he saw a contest being held for farmers.   800 participants tried to estimate the weight of a slaughtered bull. The real weight of the bull was 1198 pounds. Although none of the farmers could guess the exact weight of the animal, the average of their predictions was 1197 pounds.\n",
     "\n",
     "\n",
-    "A similar idea for error reduction was adopted in the field of Machine Learning."
+    "A similar idea for error reduction was adopted in the field of Ensemble Learning."
    ]
   },
   {
@@ -136,15 +136,6 @@
     "\"\"\"))"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "41e99f6f",
-   "metadata": {},
-   "source": [
-    "```{tableofcontents}\n",
-    "```"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "286ec2c0",
@@ -196,6 +187,24 @@
     "in-effect create a new generalized decision boundary in the bottom-right that better captures\n",
     "the true but unknown division of the feature space, resulting in better predictive performance.\n"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "20481b8f",
+   "metadata": {},
+   "source": [
+    "We have learned what ensemble learning is, and in the next chapter, we will learn some specific algorithms for ensemble learning"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "32240923",
+   "metadata": {},
+   "source": [
+    "## Acknowledgments\n",
+    "\n",
+    "Thanks to the book Ensemble Machine Learning: Methods and Applications 2012th Edition by Cha Zhang (Editor), Yunqian Ma (Editor). They inspire the majority of the content in this chapter."
+   ]
   }
  ],
  "metadata": {