Data200s Group project
Firstly, shout out to my teammate Korede Ogundele, who wrote a significant amount of code in this repository and who I've always enjoyed working with.
In this project, we combined data analysis and machine learning techniques to model air quality across various US counties. Using Python libraries NumPy, Pandas, seaborn, matplotlib, and scikit-learn, our team constructed two linear regression models and successfully conducted a comprehensive analysis of emission data.
https://ds100.org/fa23/gradproject/
https://drive.google.com/drive/folders/1AVzJyX7yv9RufLUbGUD6DUDXXUsfW5W4
https://docs.google.com/document/d/1ciCfkGh4PehvJ21IM3Me0dYCzw-nH7uvAwNrqsUQs6c/edit
https://docs.google.com/document/d/1itRKmAqeMe8nCv4MViYwHv5UWHMZBcLGdagjyv1heYc/edit
https://docs.google.com/document/d/1sE2sYOxgZfOL1DPZ-x_wRYHt0eBoZIv1RK-uFJ_Mp70/edit?usp=sharing
Originally copied from GHCN_data_preprocessing.ipynb in the dataset drive, we will likely tailor this to our needs.
See the "Emmissions questions" tab of the spreadsheet above. We can talk about transferring those questions to this readme or whatever long term organization we want.