Creating a Real State Price Predictor model using machine learning Libraries.
The data is downloaded from UCI Machine Learning repository. The dataset has approximately 14 attributes and 506 rows that are mentioned in the housing data
The coding is done in jupyter notebook in python programming language using numpy, matplotlib, sklearn, pandas and joblib libraries