Real Estate Price Prediction using Machine Learning

As a part of my semester project, I worked on a real estate price prediction project using machine learning. The project involved web scraping data from zameen.com to obtain house prices. The focus was on providing predictions for five major cities in Pakistan, namely Faisalabad, Karachi, Islamabad, Rawalpindi, and Multan. The predictions were generated based on user input for the area name, square feet, number of bedrooms and bathrooms required.

By utilizing machine learning algorithms, the project aimed to predict accurate prices for real estate properties in different localities. The model was trained on historical data of house prices and then tested on the scraped data to evaluate its accuracy. I gained valuable experience in web scraping and machine learning techniques throughout the project.

The project was a great learning experience, providing me with practical skills in data analysis and machine learning. I enjoyed the challenge of building a model that could predict real estate prices accurately, and I am proud of the results achieved. Overall, this project has enhanced my knowledge and expertise in machine learning and has prepared me for tackling more complex problems in the field.