tensorflow / tensorflow/recommenders
How to use pertained embedding as feature in the user model
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- Dominant language
- Python
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Description
Hello,
I have a signature embedding of size 256 for each user. How can I use this vector as a feature in the user model?
Any tips are appreciated.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue does not name a file, entry point, or failing test. Start by reviewing the repository's guidance and examples for user models and embedding features, then determine whether the requested use is already supported or requires a new capability; done should include a documented, working way to use a 256-dimensional user embedding.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100