Port to cloud, add automation hooks to queue up a list of experiments

[gksb88]

Port code and make sure it runs on a GCP/Azure/AWS instance.

Once done, take an input json of experiment configs and execute them. We will have to arrive on an experiment config to use.
Off the top of my head it should have:

1. Feature Engineering Flags.
   Example:
   StopWords: On/Off
   Stem: On/Off
   n-grams: 4 (This will be a continuous value)
2. Model Type (Bayes, NN, SVM. We can assume that the hyperparameters get played with internally)

This coupled with model saving / serialization. Should hold us in good stead - come December.