How we built an AI factory — Parts 2&3
How we industrialized deep learning algorithms to production by building a unique agile framework. This series explains how we create super performing models even on premise.
As I explained in Part 1 of this series, most data scientists and communications around AI focus on performances and how to get the best F1 score or mAp. However when developing AI enabled systems (especially on premise like Preligens) performances are key but they are only the tip of the iceberg.