In this repository, I conducted different machine learning techniques on four different datasets.

Classifiers

I evaluated the choices for classification of data from a brain region that activated when participants saw line drawings. I tried using different classifiers and assessed the optimal option.

Permutation Analysis

I performed a group-level permutation analysis across subjects for line drawings that activated different regions of the brain.

Clustering and LDA

I first performed k-means clustering on different news groups' data, and then conducted a linear discriminant analysis to identify meaningful topic structures within the data.

Neural Network Classifier

I designed a shallow neural network classifier to try and classify a set of images of handwritten digits. I then applied data augmentation, designed a deep network and tried classifying the digits again.