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.
Python notebooks and scripts for Great Lakes phenomena including lake breezes, upwellings, cloud cover, and buoy data.
🌊🍃 GLOW - A community-driven platform that analyzes and tracks temperatures of the Great Lakes
A sensors.AFRICA project to send SMS alerts of storms around the great lakes region. Accessible at https://stormwatch.sensors.africa/
Bayesian phylogeographic reconstruction and interactive visual analytics of Zaire, Sudan and Bundibugyo ebolavirus spread in the Great-Lakes basin
CHR-2022 data was used to analyze factors impacting mental health in five Great Lakes states.
Chris Izworski GitHub Pages profile: public projects, Great Lakes tools, Michigan reports, and verified source links.
Bay City, Michigan — Chris Izworski writes about Saginaw Bay, Great Lakes ecology, and Zone 6a gardening.
CrewCert — Marine Crew Certification Tracker. Rules engine for Transport Canada/STCW compliance, expiry tracking, Regulation Watch, and crew self-service. Single-file HTML, zero dependencies.
Great Lakes temperature analysis application developed for CPS125.
Chris Izworski GitHub project profile linking public projects, Great Lakes tools, Michigan outdoor reports, and verified identity pages.
Exploring and modeling the relationships between lake characteristics, surface temperature, and ice concentration in the Great Lakes.
Desktop SLEAP workflow manager for local labeling and Great Lakes HPC training/inference with Slurm, SSH, and task history automation.
Empirical project for Dr. Chris Stoddard's ECNS 562
data and scripts from the St. Louis River Estuary (SLRE)
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