Assignment code of AMATH582 Computational Methods For Data Analysis at the University of Washington
Exploratory and objective data analysis methods applied to the physical, engineering, and biological sciences. Brief review of statistical methods and their computational implementation for studying time series analysis, spectral analysis, filtering methods, principal component analysis, orthogonal mode decomposition, and image processing and compression.
HW1: Finding Subs (in matlab) - (tracked submarine using Fourier transform to extract the submarine frequency signature, implementing a Gaussian filter that extracts this frequency signature to denoise the data, and detecting the submarine over time.)
HW2: Classifying Digits (py) - (trained a classifier to distinguish images of MNIST handwritten digits, test our classifier performance using different model fitting methods, like K-nearest neighbors, random forest, and gradient boosted trees, and support vector machines)
HW3: Qualifying Red Wine (py) - (test regression and classification methods, apply linear regression to fit a linear model to the training set)
HW4: Classifying House Votes from 1984 (py) - (test the performance of spectral clustering and a semi-supervised regression algorithm to predict the political orientation of House members based on their voting records on 16 bills)
HW5: Image Compression and Recovery (py) - (recover the original image from the corrupted version using Compressed image recovery)
data for each jupyter notebook is found in the data folder, with corresponding pdf descriptions of each assignment found in pdf reports