Dataset

A dataset is an organized collection of examples or records used for training, evaluation, analysis, or system operation.

Plan for this page

Understand one concept in plain language and connect it to nearby ideas.

You will leave with: Datasets may contain text, images, audio, measurements, labels, metadata, or interactions. Their collection method, coverage, quality, rights, documentation, and division into training and evaluation portions affect what conclusions are justified.
Time: 3–8 min
Before you begin: No prerequisite. Keep one real example in mind.
Do this now: Read the explanation, then compare the example with the common misunderstanding.

Prepared next stepInspect data, patterns, and learning

DatasetA dataset is an organized collection of examples or records used for training, evaluation, analysis, or system operation.

Training
Label
Feature
Bias

Plain explanation

Datasets may contain text, images, audio, measurements, labels, metadata, or interactions. Their collection method, coverage, quality, rights, documentation, and division into training and evaluation portions affect what conclusions are justified.

Example

A dataset for plant recognition might contain photographs, species labels, locations, dates, and information about how each image was collected.

Why it matters

Models can reproduce gaps and patterns present in their data, and an evaluation dataset can give misleading confidence if it overlaps training data or poorly represents actual use.

Common misunderstanding

Misconception: a large dataset is automatically representative and lawful to use. Correction: size does not settle coverage, consent, quality, ownership, or fitness for purpose.

Related concepts

Follow relationships, not only the alphabet

TrainingTraining is the process of adjusting a model to improve performance on an objective using data, feedback, or interaction.LabelA label is a target value or category attached to an example for training or evaluating a supervised model.FeatureA feature is an input property or representation used by a model when producing an output.BiasBias is a systematic tendency in data, measurement, design, model behavior, or institutions that shifts results in particular directions.

Inspect data, patterns, and learning

Sources and scope

What supports this object

Machine Learning GlossaryGoogle for Developers

Defines datasets and common data splits; governance, consent, licensing, representativeness and documentation require additional context.

Open source

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