reverse-OPS

A technology paradigm in which reverse-extract-transfer-loading python into an ETL pull creates enough data to leap over machine learning and employ deep learning.

The last algorithm.

Deep-learning requires too much data to be useful practically; hence the pervasiveness of machine learning.

Spreading a Python command over a reverse-ETL pull creates enough data to facilitate the jump to deep-learning.

This is the principle behind reverse-OPS.