Welcome - To summarize my public github repositories:

• These repositories are simple projects that serve as good references. I do still share links to these repositories as examples when these topics come up in discussions.
• I don't have any machine learning models as public repositories at this time.
• Some of the repositories share optimization models that use open source (ortools or pulp rather than gurobi or cplex, etc.)

About the repositories:

• I'm currently working on weather_python, which focuses on weather data analysis in python and demonstrates some best practices.
• The sustainable supply chain template utilizes geocoding, geospatial calculations, mapping with folium, and sustainability metrics to create a supply chain template that accounts for both transportation and facility greenhouse gas emissions (rather than only one or the other).
• Python Optimization contains the following:
  • Seasonal Inventory is a multi-period inventory model with capacity constraints. The model utilizes ortools pywraplp.
  • Facility Location is a simple supply chain example combining optimization with geospatial visualization of the results.
  • Minimum Cost Flow is a supply chain model that chooses the optimal transportation lanes.
  • Oregon Districts was a project in anticipation of 2020 Census data. The project uses python optimization that is explained with an accompanying article.
• Ducks is data exploration, analysis, and metric development with R about how many eggs our ducks have laid.
• The geospatial repository contains the following:
  • One-in-covid-deaths uses geopandas to visualize comparisons with choropleth maps.
  • Montavilla Grocery Stores displays folium's geospatial capabilities while exploring grocery store locations in East Portland.
• Oregon Covid-19 contains charts about Covid-19 spread during the start of the pandemic; I wanted to know more about how the virus was spreading near me.
• Weather has multiple Historical Weather Data Analysis, mostly with R but also with python. Democratizing weather data with R is a tutorial that I wrote in Towards Data Science that shows how to download US weather data and develops several interesting charts for gardeners or weather geeks. I wrote more articles about specific weather topics as well, such as the number of consecutive days above 80, 90, 100 degrees in Portland, Oregon (article), and summer nighttime lows temperatures across 26 US cities (article).
• Portland Districts is a geospatial analysis utilizing census tract data to explore a few districting options for Portland's first potential city council districts.
• Music is a simple demonstration of how to use pydub to trim mp3 files.
• towardsDS only has one jupyter notebook that accompanied an article about presentations with jupyter slides

More

• Read my articles on Medium and Towards Data Science: https://sabolch-horvat.medium.com/ 📓
• 🚚 🚢 I work primarily on supply chain networks, but my github has a more diverse range of interests
• 🌱🌲🌳 My wife and I are gardeners and home orchardists; our ducks also help with permaculture aspects of our system 🐛🦆🥚. For duck videos, please see our youtube channel: https://www.youtube.com/c/gardeningwithducks