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All Content tagged with Amazon Personalize
Amazon Personalize enables developers to build applications with the same machine learning (ML) technology used by Amazon.com for real-time personalized recommendations – no ML expertise required.
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For **user-personalization recipe**, I have the following metadata:
* **Users:** User_id, age, gender,
* **Interactions:** User_id, Item_id, event_type,
* **Items:** Item_id, Genre and Item_title.
We...
Getting this error when trying to add filter on other metadata for interactions dataset.
"**Could not create filter: Interaction dataset supports condition on only event_type field.**" Can anyone conf...
I am having trouble with the deletion of Interactions Dataset. I was trying to delete the existing Dataset in my Dataset Group, in order to create a new one, with the boto3 delete_dataset() function (...
Is there a way that I can provide a callback function that executes when a solution version changes state to 'active' ?
Currently, my system successfully creates a new solution version, but I want to...
I am executing filter to Perzonalize, where the filterValues returns a message that the maximum length is 1000 and my filter has a length of 6664. what can I do about it so that it takes the full leng...
What is the model family/type behind Amazon Personalize's User-Personalization recipe?
I am trying to create a lambda function to automate the creation of a dataset import job in Personalize. I followed this guide: https://docs.aws.amazon.com/personalize/latest/dg/granting-personalize-s...
Hello everyone. I have a problem with the get-recommendations response. For example:
Input data (`utf-8 encoding`):
```
{'ItemId': '1', 'properties': '{'description': 'random string\\nnext line '}'}
...
Using a web console for Amazon Personalize for creating item datasets, it throws an error "GENRES field cannot be of type null" when trying to create an item schema with GENRES that contains type "nul...
Assume a short video recommendation system with a million short videos and users. The users can watch & like videos.
Using a receipt such as USER_PERSONALIZATION (Users, Video as items, and Watched/Li...
After created a Batch inference job to get Batch Recommendation I cannot figure it out how to delivery recommendation to my application (React Native) from file stored on S3 Bucket.
I was testing AWS Personalize recommenders and I realize that I was using all which charge for real-time recommendations. Is there a way to use them not for charge on real-time?