AI Foundations
Dataset
A collection of examples or records used to train, test, or evaluate a model.
Example
A retailer trains a demand model on several years of sales, prices, and promotions.
Why it matters
It gives a team a shared collection to learn from, compare results and investigate mistakes.
You'll hear it
“These records came from a different group of customers.”
Can you control it?
Sometimes
Sometimes. Teams building or customizing a system can select, clean, and limit their datasets. Everyday users may only control files or examples they choose to provide to a product.
Common questions
- What is in an AI dataset?
- It can contain text, images, audio, measurements, transactions, labels, or other examples relevant to the task.
- Does more data always make AI better?
- No. Relevance, coverage, accuracy, consent, and labeling can matter more than raw volume.
- Can a dataset contain bias?
- Yes. Missing groups, historical patterns, collection choices, and labeling decisions can all affect results.