Uber is a platform where those who drive and deliver can connect with riders, eaters, and restaurants. In cities where Uber is available we will analyze the different time series, and average hours of working and growth of uber and will calculate the price of distance travel and also will analyse different companies growth with uber and check which one is best.
We will apply machine learning algorithms that will help us to predict the price of uber for distance so company can analyze and the differenitate the prices of their and lyft company.
For this project i have used the dateset available on kaggle comprise of 57 columns and 693071 rows you can view or download dataset from here. https://www.kaggle.com/brllrb/uber-and-lyft-dataset-boston-ma
Initialy we will work on understanding dataset for EDA. We will clean the data which will needed us to EDA and we will visualize the data for better understanding.