Nedbank code challenge

##P1 The following steps should be taken to locally set-up and run a Jupyter notebooks for three ML models (namely logistic regression, SVM and kNN). These models classify users that would potentially buy a product from a product campaign.

1. Unzip nedbank.zip file
2. Open nedbank folder in IDE
3. Create a virtual environment with Python 3.6.2 (Python 3.7.0 should also work)
4. In command line run 'pip3 install -r requirements.txt' from nedbank folder root directory
5. In command line run 'jupyter notebook'
6. Open pop-up webpage and search in nedbank folder for respective ML model .ipynb file
7. File -> checkpoint -> revert to checkpoint
8. Run each cell with Shift+Enter or simply scroll to the bottom for the conclusion

##P2 The following steps should be taken to locally set-up and run a detection function that attempts to count messages that should be sent to users with particularly high spending behavior.

1. Unzip nedbank.zip file
2. Open nedbank folder in IDE
3. Run test.py to see tests cases running