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P1 House Prices - Advanced Regression Techniques

GOAL: Using the Ames Housing dataset compiled by Dean De Cock, we want to predict the final price of each home along 79 feature columns. We can find the Kaggle Competition here.

I. Imports

II. Data Cleaning and Feature Engineering

  • Numerical imputation
  • Ordinal Encoding
  • Nominal dummy variables

III. EDA & Data Visualization

IV. Apply and Grade Linear and Ensemble Regression Models

  • Compare error metrics with RMSE and R2.
  • Detect best fit
  • Check residuals