“Support Vector Machine” (SVM) is a supervised machine learning algorithm which can be used for both classification or regression challenges. However, it is mostly used in classification problems.

1. Apply SVM algorithm to the iris data and got 98% accuracy (iris dataset.ipynb)
2. Apply SVM algorithm to the breast cancer dataset and got 96% accuracy (SVM.ipynb).

1. SUPPORT VECTOR MACHINE(SVM): https://medium.com/@aqsa.qadir44/support-vector-machine-d7ccf74d313a
2. Tuning parameters of SVM: Kernel, Regularization, Gamma and Margin: https://medium.com/@aqsa.qadir44/tuning-parameters-of-svm-kernel-regularization-gamma-and-margin-5f2f6639121a