This project is concerned with applying different ML models to predict Housing prices from the given dataset. The CSV file contains the following features- longitude,latitude,housing_median_age,total_rooms,total_bedrooms,population,households,median_income,median_house_value,ocean_proximity These features are fed into scikit learn pipelines.The dataset is split into training and testing sets. We compare the results between a Linear Regression Model(Linear Kernel) and a RandomForestRegressor.