ML_real_estate

Regression problem - Predicting transaction price for a property

This project includes data cleaning, visualization, feature engineering of a real estate dataset. The dataset is first converted to an ABT (.csv) which is ready to be fed to algorithms to create different models. These models are then compared against some metrics. The winning model's pipeline object is saved as a pickle file. An excecutable real_estate.py is provided which can be run through a command line to generate a csv file of predicted values of any raw data.