House Price Prediction is a data science and machine learning project where a dataset is given and the model is trained with linear regression and the price is predicted with an accuracy of 85%. It is also deployed as a web app using the Flask web framework and HTML,CSS.
#Steps to run the project:- 1)Install the basic requirements of python library- Flask currently requires python 3.8 only,numpy,pandas,pickle. Command - pip install MODULE_NAME 2)Use VS Code to run and install Live Server extension on it. 3)Run - app.py or flask run in VS Code to create a local server which opens an html file in the browser.