This project is about the analysis of the Uber Data Pattern. The datasource is from Kaggle(https://www.kaggle.com/datasets/marcusrb/uber-peru-dataset).

I'll analyse the Uber Datapattern from three data characters: geo data, temporal data and user data. Afterwards, linear regression and randome forest will be employed to train a machine learning model to predict the price. Based on these, I'll develop a web application with flask and deploy it with Docker.