Rasa NLU in Depth - Part 1: Intent Classification

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Hi Rasa community! :sunny:

in a three-piece blog post series we want to share our best practices and recommendations how to custom-tailor the Rasa NLU pipeline for your individual contextual AI assistant.

We start the series with a blog post about intent classification, which gives you guidelines on

  • which intent classification component you should use for your project
  • how to tackle common problems: lack of training data, out-of-vocabulary words, robust classification of similar intents, and skewed datasets

Read it here: Rasa NLU in Depth: Intent Classification

In the next weeks we will publish the other two parts, namely

  • Part 2: Entity Extraction – Choose the right extractor for each entity
  • Part 3: Hyperparameters – How to select and optimize them

Lets us know what your experiences and recommendations are for the perfect intent recognition with Rasa NLU :rocket:

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