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.