Uber Technologies, Inc., commonly known as Uber, is an American multinational ride-hailing company offering services that include peer-to-peer ridesharing, ride service hailing, food delivery (Uber Eats), and a micromobility system with electric bikes and scooters. The company is based in San Francisco and has operations in over 785 metropolitan areas worldwide. Its platforms can be accessed via its websites and mobile apps.
There are more than 75 million active Uber riders accross the world. Uber is available in more than 80 countries worldwide. Uber has completed more than 5 billion rides till now. Over 3 million people drive for Uber. In the United States, Uber fulfills 40 million rides per month. The average Uber driver earns $364 per month.
Here we perform data analysis on UBER data using Machine Learning in Python.
We will be working on Uber drives dataset. The dataset is available in Kaggle or you can even download the dataset utilized in this project from here: UBER Dataset. This dataset contains 7 columns and 1156 entries.
We can perform our project analysis in four steps.
The entire code is available on Github.
I have created the blog that explains the entire implementation of the project.