The main objective of the project is to design an algorithm which will tell the fare to be charged for a passenger. Machine learning algorithms are used to develop a regression model.

The project is about on world's largest taxi company Uber inc. In these project we're looking to predict the fare for their future transactional cases. And this company deliever services to lakhs of customers daily. Now it becomes really important to manage their data properly to come up with new business ideas to get best results. So, it becomes really important to estimate the fare prices accurately.

I. To run the code in Jupyter Notebook ->first open jupyter notebook and open Uber.ipynb file in jupyter notebook ->now import all the packages if packages are not installed then first install all the packages by using "pip install packagename" command. -> once imported all the packages now set the path where train and datasets are saved. -> Now run all the codes by clicking shift+enter buttons together.

II. To run the code in Google Colab Notebook -> Copy the .ipynb link -> Open Google Colab Notebook -> Click on File -> Click on open -> Click on Github -> Paste the link in the first blank -> Search for the file -> And Open -> Now add all the required .csv files -> Now run all the code lines one after the other using the combination of Shift+Enter buttons together at a time.