Data and feature engineering · MLD-0274
Dataset
A collection of observations used for analysis, training, or evaluation.
Original reference page · detailed expansion pending. Original definitions, examples, notes and citations are preserved below. New examples are illustrative, not benchmark results.
Original example
A table of examples and labels.
Original caveat
A dataset's provenance and sampling matter as much as its size.
Context and aliases
Level: Foundational. Stages: Data · Training · Evaluation.
Tags: ML · DL · SLM · LLM.
Aliases: Data set.
Related concepts
Concepts linking here
Technology connections
- Gensim — Topic modeling and vector-space text-analysis library.
- Hugging Face Datasets — Dataset loading, transformation, caching and streaming toolkit.
- Hugging Face Diffusers — Reusable pipelines and components for diffusion-based generative models.
- Hugging Face Tokenizers — Fast tokenizer training and execution library with Rust internals.
- Hugging Face Transformers — Common interfaces and implementations for pretrained model architectures.
- OpenCLIP — Open implementation and training tooling for CLIP-style contrastive models.
- Sentence Transformers — Framework for embedding and reranking text and other supported inputs.
- SentencePiece — Language-independent subword tokenizer and trainer.
- spaCy — Production-oriented NLP pipelines and linguistic annotations.
- timm — PyTorch image-model collection with training utilities and pretrained weights.
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 ↗