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