Інформаційна система рекомендування ціни вживаного авто

Abstract

The object of research – the process of creating an informational system for recommending a used car price. The purpose of the work – to systematize modern methods of exploratory data analysis on Python, to offer the technology of analysis and price prediction for used cars and to check it according to the data from the USA and Ukraine. Comparative analysis of existing systems for recommending used car prices in Ukraine is carried out. Systematization of methods of exploratory data analysis is carried out. A comparative analysis of algorithms for solving the problem of forecasting the price of a used car is carried out. Optimal technologies for implementation of the informational system (its modules of exploratory data analysis and forecasting of the car price) are determined. The accuracy of the applied algorithms is compared. Estimated assumptions about the development of the object of study - the development of an informational system for forecasting of a used car price, which, unlike existing ones, implements an instant recommendation of the used car price based on the data entered by the user. Scope of application – web services specializing in used car sales throughout Ukraine.