PricePredictor – Real Estate Price Forecasting System

Price Predictor is an information system for predicting real estate prices, developed as part of a bachelor's thesis. The project is designed to simplify the process of housing evaluation and assist users in making decisions when buying or selling real estate.

The system allows the user to enter the characteristics of the property through a user-friendly form and receive the predicted price, price per square meter, and average cost in the selected area. All requests are stored in a database, enabling the review of prediction history and analysis of results over time.

In addition to forecasting, the project includes pages with a dataset, statistics, and data visualization of the real estate market. It features user authentication, user roles, a personal profile, and automatic login using tokens. The system is built on a REST architecture and supports integration via API.

The project combines backend, frontend, and machine learning in a single modular architecture and demonstrates practical applications of Python, Flask, and data analysis in a real web system.

Internal functions of the information system:
◉ receiving and validating user input;
◉ predicting real estate prices using an ML model;
◉ automatically generating additional features based on property descriptions;
◉ storing predictions and request parameters in the database;
◉ retrieving and filtering prediction history;
◉ working with the dataset (viewing, searching, sorting);
◉ statistical analysis and data visualization;
◉ user registration and authentication;
◉ managing access roles (user/admin);
◉ automatic login via tokens (remember me);
◉ managing user profiles and their data;
◉ providing predictions through REST API.

#flask
#python
#machinelearning
#fullstack
#webdevelopment
#information_system
#realestate
#datascience
#restapi
#portfolioproject