diff --git a/open-machine-learning-jupyter-book/ml-advanced/kernel-method.ipynb b/open-machine-learning-jupyter-book/ml-advanced/kernel-method.ipynb
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--- a/open-machine-learning-jupyter-book/ml-advanced/kernel-method.ipynb
+++ b/open-machine-learning-jupyter-book/ml-advanced/kernel-method.ipynb
@@ -66,6 +66,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "Kernel Methods is a technique widely used in the field of machine learning, especially for problems involving nonlinear pattern recognition and data analysis.\n"
     "SVMs are a powerful and flexible class of algorithms used for classification and regression. In this section, we will explore the intuition behind SVMs and their use in classification problems.\n",
     "To start with, let's understand the basic concept of SVMs. \n",
     "Support Vector Machines (SVMs) are supervised learning algorithms that can be used for classification and regression tasks. SVMs try to find the best decision boundary that separates data points of different classes. The decision boundary is chosen such that it maximizes the margin between the data points of different classes.\n",