Source code for reproducing "Predicting Dreissenid Mussel Abundance using Deep Learning" by Galloway et al..
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Updated
Jun 8, 2023 - Jupyter Notebook
Source code for reproducing "Predicting Dreissenid Mussel Abundance using Deep Learning" by Galloway et al..
Machine learning projects done as part of an online PGPML course offered by Great Learning, an ed-tech company.
Sussman A.L., Gardner B., Adams E.M., Salas L., Kenow K.P., Luukkonen D.R., Monfils M.J., Mueller W.P., Williams K.A., Leduc-Lapierre M., & Zipkin E.F. 2019. A comparative analysis of common methods to identify waterbird hotspots. MEE 10(9): 1454-1468.
A sensors.AFRICA project to send SMS alerts of storms around the great lakes region. Accessible at https://stormwatch.sensors.africa/
Exploring and modeling the relationships between lake characteristics, surface temperature, and ice concentration in the Great Lakes.
For accessing Great Lakes buoy API data. Created for GLOS Data Challenge Hackathon 2016
CHR-2022 data was used to analyze factors impacting mental health in five Great Lakes states.
Contains R codes for processing and analyzing data for Great Lakes Cladophora work
Empirical project for Dr. Chris Stoddard's ECNS 562
Great Lakes temperature analysis application developed for CPS125.
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