This project was created to predict the price of various car models based on one or the other numerical features of the car using a linear regression model.
Firstly, I extracted car price data from the IBM Skills Network url (the dataset available here is basically a cleaner version of the car-price dataset available in the uci archives) and then cleaned the dataset. Later, used statistical methods to understand the correlation between different attributes of a car vs it's price. Then I created a few Regression models to predict the car price on the basis of some of the key features of a car. Lastly, I evaluated the model using appropriate plots from seaborn library.
Pandas
Numpy
Scikit-learn
Scipy stats
Matplotlib
Seaborn