scikit-learn
Machine learning in Python with scikit-learn. Use for classification, regression, clustering, model evaluation, and ML pipelines.
npx skills add majiayu000/claude-skill-registry --skill scikit-learn-sickn33-antigravity-awesome --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Scikit-learn ## Overview 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. ## Installation ```bash # Install scikit-learn using uv uv uv pip install scikit-learn # Optional: Install visualization dependencies uv uv pip install matplotlib seaborn # Commonly used with 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 ## Quick Start ### Classification Example ```python from sklearn.model_selection import train_t
- Overview
- Installation
- When to Use This Skill
- Quick Start
- Classification Example
- Complete Pipeline with Mixed Data
- Core Capabilities
- 1. Supervised Learning
- 2. Unsupervised Learning
- 3. Model Evaluation and Selection
- 4. Data Preprocessing
- 5. Pipelines and Composition
- Example Scripts
- Classification Pipeline
Install scikit-learn using uv uv uv pip install scikit-learn uv uv pip install matplotlib seaborn Commonly used with uv uv pip install pandas numpy python scripts/classification_pipeline.py python scripts/clustering_analysis.py
What does the scikit-learn skill do?
Machine learning in Python with scikit-learn. Use for classification, regression, clustering, model evaluation, and ML pipelines.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill scikit-learn-sickn33-antigravity-awesome --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.