To ensure that the email bot learns from the training records and detects the correct information, such as topics and entities, apply the training changes to the text analytics model for the system. You apply changes to the model after you enable the training data recording, and then create and review the training records.

1. Enable training of your text analytics model for the email bot.
   For more information, see Enabling the training data recording for an email bot.
2. Improve the email bot model by providing sample training records.
   For more information, see Creating training data manually for an email bot.
3. Update the training data by ensuring that the email bot detects the right information by using text analysis.
   For more information, see Correcting training data in an email bot.
4. Optional: To move the training data to another email bot, export and import the training records.
   This action makes the email bot easier to maintain and build in production, QA and development environments. For more information, see Transferring training data to another email bot.
5. Make the email bot learn from the training data by building a text analytics model.
   This action improves the artificial intelligence of the system. For more information, see Applying changes to a text analytics model for an email bot.

   Design Patterns: For more information about NLP and machine learning in email bots, see Using email bots for natural language processing and machine learning.