JuliaAI / JuliaAI/DataScienceTutorials.jl
Add Common misconception sections to MLJTutorials
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- Dominant language
- ReScript
- Stars
- 126
- Forks
- 19
- PR merge metrics
- No merged PRs in 30d
Description
This might be helpful to new users especially those coming from sklearn.
For example misconceptions about the use of measures and what MLJ means by determistic and probabilistic responses compared to sklearn.
Contributor guide
No contributing guide indexed for this repository
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 MLJTutorials material and the existing explanations of measures and deterministic versus probabilistic responses. Identify where a newcomer-facing misconceptions section belongs, then ensure it explains the differences for users coming from scikit-learn and is covered by the relevant tutorial content.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia, scikit-learn
- Domain
- documentation
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100