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AWS Personalize - Recommender retraining questions

I'm a new user with AWS Personalize. So, I only have a few questions about recommender retraining below.

  • Currently, I focus on E-Commerce data set group and use the e-commerce use-case recommender. If I use this; It can't create a campaign right?
  • If I understand correctly this one is no need to retrain the model right? (If I use recommender above) because I read in many docs, it has only a retraining process when we use only the custom resource and create a campaign right?
  • So, when I increment the new event data, the recommender will apply the new data directly for recommendations, right? If yes, that means we don't need to focus on the retraining process for the e-commerce use case right? following this docs

that's all from my question.

Solution

  • Currently, I focus on E-Commerce data set group and use the e-commerce use-case recommender. If I use this; It can't create a campaign right?

    The recommenders for domain dataset groups automatically manage the inference endpoint for you. So the step of creating a campaign is not necessary. The service handles this.

    If I understand correctly this one is no need to retrain the model right? (If I use recommender above) because I read in many docs, it has only a retraining process when we use only the custom resource and create a campaign right?

    Correct. Training and retraining is managed by the service for domain recommenders.

    So, when I increment the new event data, the recommender will apply the new data directly for recommendations, right? If yes, that means we don't need to focus on the retraining process for the e-commerce use case right?

    You can send in new event data two ways. First, an event tracker can be used to incrementally stream in new events. In this case, Personalize will use new events to adjust recommendations in near-real-time to match the user's evolving intent (retraining is not necessary for this). Personalize will also persist those new events in the incremental interactions dataset so they are included in the next retraining.

    The other way you can send in new event data is with a bulk import of the interactions dataset. Since bulk imports replace the previous bulk import, your bulk files need to include all interaction history you want to train on and not just new interactions. Bulk imports of the interactions dataset are included in the next retraining.