How to train LightFM in production???
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- Dominant language
- Python
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- 5.1k
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Description
Hello I want to use my recommendation model in production I don't know how to train it in production scenario online/offline?? Can you guide about how to efficiently use it because I have a lot of data to cater???
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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
No files, tests, or entry points are named. Start by reviewing the repository's existing LightFM training guidance, then determine whether the request concerns online training, offline training, or both; done would require maintainers to define and document a supported production workflow for large datasets.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100