This article is a bit of a Frankenstein monster. There are too many possible target audiences for ML blogs and it seems like this post made an attempt to please

This article is a bit of a Frankenstein monster. There are too many possible target audiences for ML blogs and it seems like this post made an attempt to please everybody. This isn't a condemnation of the author, its just an impossible task. 1. Experienced ML practitioners will be unimpressed with the ML task generally (simple problem, no comparison with common models, no use of common dataset, no lit review) and wish that there was more detail in model design. 2. Inexperienced ML practitioners will be happy with the birds-eye view of NLP tasks but wish there were more implementation details. 3. Potential clients (non-technical) will get lost in the details/lingo and wish there were case studies or a vision of what this service can accomplish for them/their business. 4. Potential clients (technical) and SWEs will wish they got a better look at the GUI, got an explanation of the stack, and wonder about APIs/integration with whatever it is they already do. Perhaps this might explain why literally every other comment at the time I'm writing this is asking for additional details. Pick one or two!