House Prices: Advanced Regression Techniques - Machine learning

Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence. With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home.

House Prices: Advanced Regression Techniques - Machine learning

September 21, 2020

Data cleaning
Feature engineering
Machine learning
House price prediction with Random Forest Regression
Public Score - 0.14550

Link to project