scikit-learn - Machine learning workflows with scikit-learn
Build and evaluate classification, regression, clustering, dimensionality reduction, preprocessing, and model-selection workflows in Python.
Tags
Updated: 2026-10-08Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Build classification models
- Build regression models
- Perform clustering analysis
- Reduce feature dimensionality
- Preprocess mixed data
- Train machine learning pipelines
- Evaluate model performance
- Tune model hyperparameters
- Detect anomalies and outliers
- Apply ensemble methods
Inputs
- Training datasets
- Target labels
- Feature data
- Task specification
- Model configuration
- Evaluation settings
Outputs
- Predictions
- Cluster assignments
- Reduced-dimensional representations
- Evaluation metrics
- Classification reports
- Trained models
- Prediction pipelines
- Saved model artifacts
Requirements
- Python runtime
- scikit-learn library