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a small collection of python scripts written as a GMU research assistant

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A Collection of Scripts Written as a GMU Research Assistant

Some of the scripts created for George Mason Univesity as Research Assitant. The files were mainly created to explore machine learning techniques on provided data to determine which methods would work the best. Many of the scripts process data and run ceratin machine learning models (from Logistic Regression to Random Forests Classifiers to Statistical Models). Most of the machine learning done was supervised learning, with a few attempts to preprocess the data using unsupervised methods. Additionally, some signal processing methods were created such as STAMP (an algorithm to compute the Matrix Profile) are implemented. The STAMP algorithm was created from https://www.cs.ucr.edu/~eamonn/MatrixProfile.html.

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