In this Repository, I have uploaded codes for some of the projects/assignments done in class "Learning From Data".

Assignment 3 incudes codes for RDA and LDA. It also includes a code to determine a handwritten digit. Each Data point represents a 28x28 grayscale image for handwritten digits. We used 1-Nearest Neighbor as a classifier.

Assignment 4 is about using Naiive Bayes to classify text documents from the classic 20newsgroup dataset.

Assignment 5 is about working with a real-world dataset, that can be downloaded from kaggle.com/c/sf-crime. The dataset contains information about various incidents/crimes in San Francisco. Here we use l_2 reularized multiclass logistic regression classifier to predict the type of a crime based on the hour of day, day of the week and Police department district of the incident.