Collection of assignments for Amath482:Computational Methods for Data Analysis course. Taken at the University of Washington Winter of 2020 from instructor Craig Gin.
Preformance in the course was based on 5 projects, each of which done in either MATLAB or Python focusing on a select few skills fundamental to data science.
This repository is split into 5 subdirectories each containing code and supporting files for a piticular assignment:
hw1 - Employs the Fast Fourier Transform for noise filtering of 3D data.
hw2 - Uses the Gabor Transform to explore sprectrograms and produces musical scores for audio recordings
hw3 - Uses techniques from video processing and principal component analysis to get spacial data from several videos.
hw4 - Uses spectral methods, principal component analysis, and linear discriminant analysis for music classification.
hw5 - Explores both dense and convolutional nural netwroks for image classification using the Fashion MNIST data set.
Within each repository is an additional README with additional information about the assignment and neccessary resources for the provided code. Repository is maintained by Tanner Graves.