microsoft / microsoft/dstoolkit-mlops-v2
Consider adding reference implementations for one of each of a supervised and unsupervised ML models
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Nobody has claimed this yet.
enhancement
- Dominant language
- Python
- Stars
- 33
- Forks
- 17
- PR merge metrics
- No merged PRs in 30d
Description
We currently have two linear regression models, a supervised learning technique, would it be more useful to have at least one of each of the following:
Supervised
- regression model
- classification model
Unsupervised - clustering model
- any deep learning model (supervised or unsupervised)
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
Start by reviewing the repository's two existing linear regression models and how reference implementations are organized. Determine the expected scope for supervised regression and classification, unsupervised clustering, and a deep learning model, then confirm the examples are runnable and documented consistently with the existing models.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100