Data and feature engineering · MLD-0055
Annotation
Adding human- or machine-produced target information to examples.
Original reference page · detailed expansion pending. Original definitions, examples, notes and citations are preserved below. New examples are illustrative, not benchmark results.
Original example
Mark entity spans in documents.
Original caveat
Annotation guidelines define the task as much as labels do.
Context and aliases
Level: Intermediate. Stages: Data · Training · Evaluation.
Tags: ML · DL · SLM · LLM.
Aliases: Labeling.
Related concepts
Concepts linking here
Technology connections
- Argilla — Human feedback and dataset-curation platform.
- Cleanlab — Data-centric tools for finding label and other dataset issues.
- CVAT — Computer-vision annotation tool.
- Docling — Document parsing and conversion toolkit.
- FiftyOne — Visual dataset exploration and evaluation application.
- Great Expectations — Data validation framework using declarative expectations.
- Label Studio — Configurable data-labeling application.
- Pandera — DataFrame schema and statistical validation library.
- TensorFlow Data Validation — Dataset statistics and anomaly-detection tooling.
- Unstructured — Document ingestion and partitioning toolkit.
Original references
- scikit-learn: cross-validation ↗ · Reference link
- scikit-learn: missing-value imputation ↗ · Reference link
- scikit-learn: preprocessing ↗ · Reference link
- scikit-learn: feature selection ↗ · Reference link
- Original reference URL ↗