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chicago-communities

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Exploring the impact of socioeconomic indicators on hardship in Chicago neighborhoods using machine learning. Leveraging Linear Regression, Decision Tree, random forest, and Agglomerative Clustering, the project identifies key factors—unemployment, lack of a high school diploma, and poverty—highlighting disparities in the dataset from 2008-2012

  • Updated Dec 16, 2023
  • Jupyter Notebook

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