The objective of this Project is to predict the likelihood of a person having an account.

##Table of Content

• Instalations
• Project Motivation and Description
• File Description
• Observations and Results
• Limitation
• Licensing, Author, Acknowledgement

The code requires Python versions of 3.* and general libraries available through the Anaconda package.

predict the likelihood of the person having a bank account or not (Yes = 1, No = 0), for each unique id in the test dataset . Training the model on 70% of the data and test your model on the final 30% of the data, across four East African countries - Kenya, Rwanda, Tanzania, and Uganda.

This project includes one Jupyter notebooks, one pickled files,. The .ipynb file titled 'Financial_inclusion.ipynb' contains the code that creates the c>

There are a number of limitations of this project and the chosen implementation:

• Experiment was only done on limited available data.

The data used for the analysis comes from:

• Zindi

Feel free to use the code as you please and play around with it.