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Veena Krishnamurthy (VeenaKrishnamurthy)
Deloitte Australia

Deloitte Australia
VeenaKrishnamurthy Member since 2018 10 posts
Deloitte Australia
Posted: October 2, 2018
Last activity: May 9, 2019

How to train the NLP models to learn automatically from the feedback provided?

Hi Support Team,

I have read the below articles and aware of how the models can be updated with feedback loop manually by a data scientist post reviewing the data.

However, can anyone let me know if there is a way to update the models with the feedback data automatically without having the intervention of any user?

Below is the scenario where I am currently working on :

Run the NLP models(Topic detection) on the input data and try to match relavant category based on keywords provided in the Taxonomy sheets. If the category is not found the case routes to a user who will update the relavant category and move the case ahead. This data will be written into the Training models as well.

The only way I see to put this feedback data into the model to learn is to run the update model wizard again manually. Is there an automated way to input the feedback data into model without having to run the update model wizard manually?

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