I agree with Francine. The quality and diversity of the training data used to develop the ML Extractor is a key factor in determining its performance. Popularity and cost shouldn't be the primary drivers here.
Option B seems the most logical choice. Considering the document types, language, and data quality is crucial for ensuring accurate and reliable extraction results. The ML Extractor needs to be tailored to the specific use case, not just the most popular or cheapest one.
Sharee
2 hours agoFrancine
17 days agoJoseph
20 days agoCristal
22 days agoAlpha
24 days ago