mne-tools / mne-tools/mne-python
ML Documentation: what's missing
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- Dominant language
- Python
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- Forks
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- Avg merge
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- Merged PRs (30d)
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Description
Here is a proposal in the todo for the MVPA/Decoding-Encoding/ML module.
- a brief tutorial on ML to introduce the key concepts (fitting, predicting, scoring, CV)
- a tutorial on model interpretation and its limits: when can you do patterns, what does it mean, what are the risks
- a tutorial to highlight the importance of supervised spatial filter for oscillatory activity
- a tutorial to highlight importance of supervised spatial filters for various types of artefacts
- a tutorial to do source decoding and its risks
- a tutorial to explain pipeline with 2D, 3D, 4D tensors
Please comment and I'll update the proposal.
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 proposal for the MVPA/Decoding-Encoding/ML module and the listed tutorial topics. Clarify which topics are in scope and what each tutorial should cover before writing documentation. Done means the agreed tutorials are added and the proposal's corresponding items are complete.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- machine-learning, python
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100