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analytics-sandbox

Machine learning models w/ scikit-learn

structure

  • / (root): ML on real scenarios
  • /dataset: .csv files
  • /probability: core probability exercises
  • /statistics: core statistic exercises
  • /pandas: core pandas concepts, intersection b/w pandas and numpy
  • /opencv: core image and video concepts w/ opencv
  • /numpy: core image concepts in matplotlib and numpy
  • /scikit-learn: core ML concepts w/ scikit-learn

models at / (root)

  • car_sales_lineer_regression covers all ML steps
  • advertising_EDA uses precleaned click dataset.
  • real estate in NYC is very massy! dataset.
    • real_estate_of_nyc_EDA, covers explatory data analysis
    • real_estate_of_nyc_lineer_regression, sale_price prediction
    • real_estate_of_nyc_knn, to set empty neighborhoods