how many times a model makes a correct prediction

taking responsibility for how a model behaves and being honest about its performance, limitations and potential impact on others

a short report on how a machine learning model works, how well the model performs and what people should know before using the model

Documenting and evaluating a machine learning model

Computing

This unit is designed to develop pupils programming skills in a new engaging context: physical computing, using the BBC micro:bit. They will get acquainted with the host of components built into the micro:bit, and write simple programs that use these components to interact with the physical world.

Machine learning using the micro:bit

a code file that trains a machine learning model

a short report explaining how a model works and performs

What is a model card in machine learning?

A model card helps users understand a machine learning model’s purpose, accuracy and {{}}.

A confusion matrix visually represents how a model’s {{}} compare to actual values.

It allows programmers to avoid responsibility for errors.

It helps developers be open about the model's limitations and mistakes.

Why is accountability important in machine learning?

If a model correctly classifies 27 out of 30 test examples, what is its accuracy?

how often a model makes correct predictions

a table showing correct and incorrect classifications

taking responsibility for a model's performance and fairness

a document explaining a model’s purpose, accuracy and limitations

the number of times a model has been trained

the level of certainty required for an input to match a class

the speed at which a machine learning model processes data

What is a recognition point in a machine learning model?

What is the default recognition point in CreateAI?

it might be too quiet to hear in a noisy environment

Why might sound not always be the best feedback method?

the order in which a program executes instructions

{{}} blocks can be used in MakeCode to program machine learning applications on a micro:bit.

A certainty value in machine learning is expressed as a {{}}.

This lesson will be removed by end of Summer Term 2025.

Documenting and evaluating a machine learning model

Lesson outcome

This lesson will be removed by end of Summer Term 2025.