Machine Learning with Swift

Prototype creation

It is important to understand the difference between tools for prototyping and production, because very different requirements are imposed on the instruments during these two stages. Choosing the right tools for the right tasks will save you a lot of time.

During the prototyping phase, you want to be able to test your hypotheses and conduct experiments quickly. That is why it is reasonable to choose a flexible programming language within the reach of the environment, such as Python or R. You also want to have tools for data visualization and model debugging. This is something that the Swift ecosystem is still weak at. The matters of model size, speed, and stability may be secondary during prototyping (which doesn't mean ...