The project is based on Supervised Machine Learning methods, namely, Linear Regression with optimization methods. The dataset of the project was collected using Web Scrapping tools of Python programming language (Beautiful Soup and Scrapy) from turbo.az. Firstly, I analyzed and preprocessed the collected dataset using exploratory data analysis (EDA) and feature engineering techniques. In the next step, I wrote Linear Regression model with Gradient Descent optimization algorithm and with Normal Equation from scratch to train the model to predict the car prices (continuous variable). In the final step, I also trained the model using sklearn library and compared these two ways of regression modeling.