Date of Award

5-26-2018

Document Type

Thesis

Degree Name

Bachelor of Science (B.S.) in Computer Engineering and University Honors

Department

Electrical and Computer Engineering

First Advisor

Douglas Hall

Subjects

Machine learning, Neural networks (Computer science), Open source software -- Security measures -- Evaluation

DOI

10.15760/honors.540

Abstract

This paper examines the history and current state of machine learning. It examines neural networks, theory behind neural networks, how they are implemented, and how they are used. The systems and networks examined have up to three modes of learning. Theory behind machine learning is broken up into three approaches; rule-based, Bayesian, and neural networks. Operation of machine learning algorithms has been enabled by several prevalent libraries in the open source community, as well as various hardware technologies. Due to this surge in resources application developers have been able to apply machine learning in novel ways. An application of machine learning to evaluate the security practices of open source software was undertaken as the culmination of this thesis.

Persistent Identifier

http://archives.pdx.edu/ds/psu/25207

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