1. Introduction

2. Mercer Kernel and Spaces in Functional Analysis

3. Mercer's Theorem and Feature Map

4. Characteristics of Kernels

5. Well-known Kernel Functions

6. Kernel Centering and Normalization

7. Eigenfunctions

8. Kernelization Techniques

9. Types of Use of Kernels in Machine Learning

10. Rank and Factorization of Kernel and the Nyström Method

11. Conclusion