In this, I have present t a brief introduction to SVM and discuss SVM properties. In the beginning, I try to define SVM and try to identify as to why SVM with a brief overview of SVM model. The applications of SVM are presented, and for implementation, SVM is analyzed using the algorithm. ESVM areas are included. Support Vector Machines (SVMs) are competing with Neural Networks as tools for solving pattern recognition problems. I have additionally added the BPNN and KNN features.I assume this paper really examined and also understand the working of Backpropagation neural networks and have some background information of K-Nearest Neighbor Algorithm. Finally, some conclusions on SVM are added.