Logistic Classifier Deployed as Rest API using flask

Files:

1. iris_classification_model.ipynb : A simple Logistic regression model for Iris dataset
2. app.py : Flask application to deploy the model and the RESTful API
3. calling_api.ipynb: Notebook to call the API.

Execution order:

1. Run the app.py to start the webservice.
2. Use calling_api.ipynb to call the webservice. Change the 'features' list to predict the flower type. The featues list takes 4 values.

Note: If you wish to use a different model or retrain the model use the iris_classification_model.ipynb to do so.