how is countvectorizer used in real production environment?

do you keep training the model with new features/vocabulary everyday and save the vocab into a flat file and reload them up on the next day?

do you use a pipeline to streamline the process?

what is the best practice?

we are going to implement a combination of countvectorizer,tfidf and some machine learning algo in production system soon and any tips or practical experiences will be appreciated.



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