bio-microbiome-taxonomy-assignment
Taxonomic classification of ASVs using reference databases like SILVA, GTDB, or UNITE. Covers naive Bayes classifiers (DADA2, IDTAXA) and ex…
Maintainer K-Dense Inc. · Last updated April 1, 2026
This skill provides comprehensive guidance for machine learning tasks using scikit-learn, the industry-standard Python library for classical machine learning. Use this skill for classification, regression, clustering, dimensionality reduction, preprocessing, model evaluation, and building production-ready ML pipelines.
Original source
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/scikit-learn
Skill Snapshot
Source Doc
uv uv pip install matplotlib seaborn
uv uv pip install pandas numpy
## When to Use This Skill
Use the scikit-learn skill when:
- Building classification or regression models
- Performing clustering or dimensionality reduction
- Preprocessing and transforming data for machine learning
- Evaluating model performance with cross-validation
- Tuning hyperparameters with grid or random search
- Creating ML pipelines for production workflows
- Comparing different algorithms for a task
- Working with both structured (tabular) and text data
- Need interpretable, classical machine learning approaches
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