1. Support Vector Machine (SVM): draw a fat line, like a wall, to classify data set into different categories, dots are support vector and it is used to solve over-fitting problem (vs logistic regression).
Non-linear data set can be “converted” to linear ones with Kernel, which is like a goggle, look at the world in a different angle (dark to light).
2. Naive Bayes Classifier