Using colors to predict whether this is Pikachu or Bulbasaur…
The deployment environments of a machine learning (ML) model are changing. In recent years, we went from locally training models and running them on standalone scripts to deploying them in massive and specialized setups. However, the industry hasn’t been focusing only on large-scaled-productionized ML, but also its small, portable, and accessible counterpart—for machine learning has found a place in embedded systems.