This Project is based on Machine Learning in which We calculate Price of the House using a Dataset and training it by using several Machine Learning Algorithms Like EDA(Exploratory Data Analysis) and SEMMA(Sample, Explore, Modify, Model, Assess) model.
The Model takes several factors like lot size, Number of Rooms, Floors, Bathrooms etc and hence Predicts the Price with 95% Accuracy in USD.
A. Python Script
-> Libraries used :
-> Consist of 11 Independent Variables & (Price) as Dependent Variable. -> Model Used : Linear Regression
B. Server-side Script
-> Get Requests for 11 inputs(Independent Variables) -> Send Request for Predicted Price(Dependent Variables) -> Web Server used : Apache2