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ModelsIntermediate1950s

Training

Model Training

Training is the process of teaching an AI model by showing it data and adjusting it when its results are wrong.

Explained simply

Training is the process of teaching an AI model by showing it data and adjusting it when its results are wrong.

1Data examples
→
2Make prediction
→
3Measure error
→
4Adjust model

At a glance

Category
Models
Difficulty
Intermediate
Introduced
1950s

Real example

A model is shown millions of examples and repeatedly adjusts itself to make better predictions.

Why it matters

It gives you a clear way to understand where this idea fits in AI and how it affects the tools you use.

Timeline

Origins

The ideas behind Training begin developing.

1950s

Training becomes a recognised term or technique.

Wider use

Research and practical applications increase.

Modern AI

Training becomes connected to newer AI systems and products.

Today

Training remains relevant in the models area of AI.

Dates for broad concepts may describe the period when the idea emerged or became widely used, rather than one exact invention date.

Learn next

Continue with these connected terms:

DatasetA dataset is an organised collection of examples or information used to train, test or evaluate AI.→ParameterA parameter is a value an AI model learns during training. Together, its parameters shape how it responds.→InferenceInference is the moment a trained AI model uses what it learned to produce an answer or prediction.→

Simple infographic

A quick visual way to understand Training.

1Data examples
→
2Make prediction
→
3Measure error
→
4Adjust model
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