MetOffice / MetOffice/ml_weather_tutorial
Notebook improvements: 02_ml_pipeline.ipynb
- Dominant language
- Jupyter Notebook
- Stars
- 4
- Forks
- 2
- PR merge metrics
- No merged PRs in 30d
Description
1. More spacing in text
2. Avoid italics
3. More comments in code to explain code
4. `list(falklands_df.columns)` is the line necessary - as the output is very long
5. train/test split - could be clearer - test/train split 20% and 25% is confusing
6. Explain features even if they are small e.g. `%%time`
7. Consider if using [`sklearn.metrics.confusion_matrix()`](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html) and [`sklearn.metrics.ConfusionMatrixDisplay()`](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.ConfusionMatrixDisplay.html) could make code simplier?
Contributor guide
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Research direction
Open 02_ml_pipeline.ipynb and review its markdown and code cells in order; first run the notebook to understand the current outputs and train/test split. Address the requested presentation, explanations, output handling, and confusion-matrix considerations, then rerun it to confirm the tutorial remains coherent.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, pandas, python, scikit-learn
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100