Identification using Keystroke

• Multiple ML model deployment as a single restful API.

• Data is keystroke testing of customers and models are used to classify these customers into categories depending on their keystrokes.

• The data and model development is done in the Jupyter notebook file.

• The restful API is built in the app.py file.

• The binary files (.pkl) contain the 3 models: RF, SVM and XGBoost.

• The result is hosted on Azure and can be accessed with https://keystrokeuser.azurewebsites.net