The name of the project is Real Estate Price Prediction which predicts the prices based on the entities provided.
The dataset consists of various amenities of a real estate of King County. The user is able to add their requirements for the house and the
model successfully predicts the price according to the provided data.
This repository contains all the associated work that has been done for the area which includes: gather housing data Notebooks associated with data engineering Exploratory Data ANalysis , Machine Learning Modeling and Web platform where user enters the data and the predicted price is shown.
1) performed EDA on house dataset
2) used various ML models to test and predict the model's accuracy
3) generated and saved the model as a pickle file
4) loaded the model from flask and rendered to the browser using Flask framework
python -m venv env
pip install -r requirements.txt
flask run
Default it runs on : [http://127.0.0.1:5000]