Automation of Data Analysis and Web-Scraping to Value Old/Used Items ( Currently working for cars only )

The heart of PriceScout lies in its dynamic approach to data collection. Through web scraping, the platform gathers real-time information from diverse online sources, staying abreast of market trends and influencing factors. The integration of machine learning algorithms adds a layer of sophistication, analyzing device specifications, market demand, and other parameters to generate accurate estimates. The objective of this project is to develop an application that can help users determine the optimal price for second-hand items they want to sell. The application requires the user to enter a description of the item they want to sell. The input data is then stored in a database for further processing. The web scraper then scans different online marketplaces for similar items and the ML module determines their current prices. The application uses this data to calculate the optimal price for the user's item.