machine learning the two big types of machine learning techniques supervised--learning that requires labeled data unsupervised--learning that doesn' require labeled data but is usually less accurate or reliable than supervised learning semi-supervised learning is in between those techniques and is used when only small portion of the data is labeled two case studies demonstrated supervised and unsupervised learningrespectively our first case study made use of naive bayes classifier to classify images of numbers as the number they represent we also took look at the confusion matrix as means to determining how well our classification model is doing our case study on unsupervised techniques showed how we could use principal component analysis to reduce the input variables for further model building while maintaining most of the information