I wanted to start a broader community experiences thread around Natural Language Processing.
A useful angle is deployment, but it also connects with testing. Different tools and workflows can produce very different results even when the goal is similar.
It would be interesting to compare practical examples, experiments, setups, or lessons that show where Natural Language Processing is genuinely useful and where it still needs improvement.
A useful angle is deployment, but it also connects with testing. Different tools and workflows can produce very different results even when the goal is similar.
It would be interesting to compare practical examples, experiments, setups, or lessons that show where Natural Language Processing is genuinely useful and where it still needs improvement.