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