The intent of the project is to create a machine learning model. I have generated model using supervised learning and aim is to do predictive analysis to predict housing price. A house price prediction engine works on the basis of data collected , consisting of 243 independent features and 1 dependent feature.
The model creation, data cleaning and finalized dataset can be found in the .ipynb file.
The crucial packages required are numpy, pandas, matplotlib and sklearn.