shalini180 / simple_bank_note_authentication

Simple_Bank_Note_Authentication

This is a simple Bank Note authentication Project that classifies notes based on entropy,curtosis,skewness and variance. The dataset is taken from kaggle competition and Random Forest Classifier is used to train the model. An accuracy of 98.78 percentage is obtained. The front end is developed using flassger whose community support is provided https://github.com/flasgger/flasgger . Flassger can be used when there is minimal need of frontend. This is a simple project deployed in flask. For seeing the webpage in your localhost: 1)Run the jupyter notebook 2)obtain the pickled file 3)run the app.py in the anaconda prompt 4)take the local url and paste it in the browser,in addition to it add apidocs(For example:http://127.0.0.1/apidocs)