ML-End-to-End

This is an End-to-End bare minimum boilerplate Machine Learning application.

Steps...

1. Loads a toy dataset
2. Performs dummy preprocess step through a data wrangler middleware
3. Trains a model and saves it to disk
4. Prediction service uses data_wrangler middleware to preprocess and predict the requests received through a Flask REST API layer.

Application contains...

File	Purpose
ML Classifier Sample.ipynb	The classifier, where model is trained
data_wrangler.py	Represents middleware to pre-processes data. Consumed by both, training and prediction steps
Prediction Service.ipynb	Flask REST API which consumes trained model through data_wrangler
iris_clf_model.pkl	Model saved to disk