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The micro:bit machine learning tool lets you
train, test and improve a machine learning

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model that can recognise different actions,
or movements.

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Here’s a quick tour of how it works.

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You’ll need two micro:bits.

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You’ll hold or wear the first micro:bit.

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Follow the instructions on screen for setting
up micro:bit 1.

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Then unplug it and attach a battery pack.

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If you have a wrist strap, you can attach
micro:bit 1 to your arm.

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The second micro:bit stays connected to your
computer with a USB cable.

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Follow the instructions on screen for setting
up micro:bit 2.

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At the bottom of the screen you’ll see live
movement data from micro:bit 1’s
accelerometer sensor.

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Each coloured line represents a different
direction, or dimension, you’re moving the micro:bit in.

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Step 1, add some data!

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Decide which actions you want the micro:bit
machine learning tool to recognise.

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Clapping and waving are good ones to start
with.

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Name your first action, then start moving!

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Click the red button to collect your first
sample of data.

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Collect at least three samples
of your first action.

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And do the same for at least one other action.

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Step 2, train the model.

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This means that the machine learning tool
makes a set of rules to estimate which action

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you’re doing when moving micro:bit 1.

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Step 3, test the model.

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Try making each of your actions.

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The screen shows which action the model estimates
that you’re making.

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The percentage number is how confident, or
sure, the model is.

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Now try it yourself and see what different movements you can train the micro:bit machine learning tool to recognise.