Classifying images from MNIST database

We implement three different types of classification methods on the MNIST dataset which consists of tens of thousands of hand-drawn images of digits from 0-9. The three methods we cover are Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), and Decision Tree classifiers. These methods delivered reasonable results in terms of their accuracy in classifying between the 10 digits, but these classification methods are outclassed by the more modern neural networks.