We are using ML when we need external data to reach a working product because it would be impossible to solve it with the regular for/if/loops. What are the next steps? Moreover, what about Test, Release, and Deployment?

Our Organizations may be “data-driven”, but now the impact we seize is bigger than we can imagine. No Link Found If you are using an ML component, misused/dirty/problematic data will affect not your internal reports as before… but your application deployment and quality of service.

Let’s discuss some AI implementations stories (its advantages/problems) finding common mistakes and future challenges for such a hyped theme.