NVIDIA-Merlin / NVIDIA-Merlin/Merlin
POC on how to build a session-based recommendation pipeline that can deal with the item cold-start problem
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Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 907
- Forks
- 129
- PR merge metrics
- No merged PRs in 30d
Description
This issue has no description.
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 provides no files, tests, entry points, or implementation requirements to start from. First clarify the intended session-based recommendation pipeline, how item cold start should be handled, and what datasets and evaluation criteria define a successful proof of concept.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100