Goal of project Using Linear Regression from Supervised Machine Learning Algorithm to learn the data from cars.csv and predicting the car prices. Tools or languages used project is created using python 3. other modules used are flask, sklearn, pandas, mysql. working frontend when a user enters the data of required car in web application, data is sent to backend, predictions are done based on previoues learning and returns a predicted price to the user. working backend Data is fed to machince learing after performing Exploratory data analysis i.e. exploring data, understanding every feature, its use or relation with traget price, finding invalid values, replacing or making them null, filling or removing values based on their importance. features with object datatype are encoded into int or float for further calculations. data is sliptted into training and testing data which are then fed to machine to learn and also calulate their accuracy. based on that a model is created to predict the values enter by the user in web application. web application is linked to python and html through flask.