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supervised-machine-learning

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Data visualization of the NYC restaurant data, and data analysis to gauge if a restaurant located in a high-income area receives a higher health inspection grade. Uses Python (Pandas, Scikit-learn, Imbalanced-learn), PostgreSQL, SQLAlchemy, Tableau, JavaScript (Plotly.js library), HTML, CSS, and Bootstrap.

  • Updated Oct 19, 2022
  • JavaScript

The Supervised Land Cover Classification (SLaCC) tool is a Google Earth Engine script created by the Summer 2019 Southern Maine Health and Air Quality Team. It uses NASA Earth observations, the National Land Cover Database, land cover classification training data, and a shapefile of Cumberland County, Maine, USA. The goal of the project was to e…

  • Updated Feb 11, 2022
  • JavaScript

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