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Area · Data & Training

Every term in Data & Training

Datasets, labelling, evaluation and the training loop itself.

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The Other Areas

8 subject areas across 32 definitions — start wherever you already are.

Machine Learning

The core ideas behind systems that learn patterns from data.

7 terms

Deep Learning

Neural networks with many layers, and the machinery that trains them.

5 terms

Natural Language

How machines read, generate and reason about human language.

7 terms

Generative AI

Models that produce new text, images, audio or code.

4 terms

Computer Vision

Making sense of images and video.

1 term

Data & Training

Datasets, labelling, evaluation and the training loop itself.

1 term

Ethics & Safety

Alignment, bias, interpretability and the limits of these systems.

3 terms

Infrastructure

Serving, scaling and running models in production.

4 terms
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Questions

Frequently Asked Questions

FAQ

Who writes these definitions?
They are written and reviewed by the AIToolsay editorial team. Every entry records when it was last reviewed, and entries that cite a specific paper or standard link to it under Sources.

How do you decide what counts as a term?
If you would plausibly hit it in a paper, a product page or a job description and have to look it up, it belongs here. We prefer one well-written entry over three overlapping ones, which is why synonyms redirect to a single canonical page rather than becoming their own stubs.

Why do some terms redirect?
“LLM” and “Large Language Model” are the same idea, so one of them is canonical and the other sends you there. That keeps the definition in one place instead of letting two copies drift apart.

What do the difficulty levels mean?
Beginner assumes no maths. Intermediate assumes you are comfortable with the basics of machine learning. Advanced assumes linear algebra and some familiarity with the literature.

Can I suggest a term or a correction?
Yes — use the link at the bottom of any entry. Corrections with a source attached get looked at first.