Uber Price Prediction System

Bharti Vidhury, Ritwik Kandwal, Harshita Aggarwal, S Danishwaran, Aditya Pande

Abstract: Uber is one of the most popular ride - sharing services in the world. To provide the best service possible to the customers, this Uber price prediction system will use a combination of machine learning algorithms and historical data to accurately predict the cost of a ride. Nowadays, Taxi services are the primary methods of transportation. The businesses have gone under the rapid transformation and moved towards the digital innovation. In the past, product developers at software businesses have created a variety of ways, but they did not take into account the need for a customer's transportation in a certain area. In order to develop a precise model for forecasting future pricing, the Uber price prediction system will examine historical trip data, traffic, weather, time of day, and other pertinent information. To produce its predictions, it will employ a range of methods including linear regression, decision trees, random forests, and gradient boosting.

Keywords: Uber, supervised machine Learning, business, price prediction, forecasting future pricing and ride-sharing