Application that predicts the price for a certain vehicle given some particular features extracted from Milanuncios.
The project is divided mainly in two different notebooks:
- MilanunciosScraper - parametrized functions that read a listing of vehicles provided from Milanuncios. Parameters are the first and last page numbers we want to read, as well as the base url.
- VehicleDataAnalyzer - notebook for data preprocessing and performing machine learning algorithms over the extracted data. A sample vehicle listing is also provided.
The most important technologies that are being used in this project are, among others:
- Python - programming language that lets you work quickly and integrate systems more effectively.
- Pandas - fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
- scikit-learn - simple and efficient tools for predictive data analysis.
- Matplotlib - comprehensive library for creating static, animated, and interactive visualizations in Python.
- Seaborn - Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.
- Selenium - suite of tools for automating web browsers.
- BeautifulSoup4 - Python library for pulling data out of HTML and XML files.
All of the descriptions above are taken from their respective official websites.
Vehicle-Price-Prediction is constrained to the following license: