# What is Dataset? Definition & Technical Mechanics

> **Source:** [SPIDITS AI AI Glossary](https://spidits.com/ai-glossary)  
> **Category:** Foundational AI  
> **Canonical Citation:** [https://spidits.com/ai-glossary/dataset](https://spidits.com/ai-glossary/dataset)

## Definition
A Dataset is a structured collection of data points, features, and target values used to train, validate, and evaluate machine learning models.

## Architectural Mechanics & Deep Dive
A dataset is a structured collection of data points, observations, or records used to train, validate, and test machine learning models. Datasets are typically split into three subsets: a training set (used to adjust model parameters), a validation set (used to tune hyperparameters and prevent overfitting), and a test set (used to evaluate final generalization performance). The quality, diversity, and size of the dataset are critical determinants of a model's capabilities.

## Industry Applications & Real-World Use Cases
Model training pipelines, data cleaning, and benchmarking algorithms.

## Frequently Asked Questions

### What are the three splits of a dataset in machine learning?
The training split (used to optimize weights), the validation split (used to select hyperparameters), and the test split (used to perform final accuracy checks).

### What is the difference between structured and unstructured datasets?
Structured datasets are organized in tabular grids (like CSV files or database tables). Unstructured datasets contain raw media like text files, audio clips, or image directories, which require preprocessing.

## Related Terminology
- [training-data](https://spidits.com/ai-glossary/training-data)
- [validation-data](https://spidits.com/ai-glossary/validation-data)
- [dataset-curation](https://spidits.com/ai-glossary/dataset-curation)

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*From the SPIDITS AI Knowledge Base (300+ terms indexed). Explore full technical definitions: [https://spidits.com/ai-glossary](https://spidits.com/ai-glossary)*