how does rasa do data cleaning?..can anyone explain how rasa do data cleaning?
Could you please elaborate on what the
data cleaning is?
In machine learning there is a topic called data cleaning…and I wanted to know how that things works in rasa
Rasa Open Source has tools that helps to evaluate the training data set (like
rasa test), but that doesn’t exclude the standard ML practices one should user (like data cleaning you’ve mentioned).
am kind of develping a chatbot for school project and choosed rasa to develop the chatbot…and on my document there is a title for data cleaning and normalization so to write that i wanted to understand what these things means to you guys to rasa nlp developers,hope u got me @degiz
there is a title for data cleaning and normalization
When you train your NLU and Core models, Rasa Open Source will tokenize and featurize the training data, but there’s no exposed tool for normalization. Also note, that the training data Rasa Open Source expects is not in a normalized format, it’s a text.
As for the data cleaning, there’s also no built in tool for that in Rasa Open Source.
I hope that helps!
okay thanks @degiz …but i was confused here where i was wingling around in the forum try to find answer and i find somone said that if we want to use a dataset we have to clean it in to nlu and stories file and could that be one thing???