pipeline for kaggle.

[nicolaepetridean]

1. create infra for splitting the data in 2 : one for public, one for pivate.
2. separate flows for training pipeline vs notebook to be executed.
3. create #dataviz graphs as output for prediction, training, and eda (extract data for usage later on ELK)
4. organizing a bit the code