Explaining the Tinkercad microbit Neural network

In a previous post, I looked at developing a neural network in Tinkercad around the Microbit (details available here) and the whole model can be found at  https://www.tinkercad.com/things/hPV4nU0Asr5-smooth-bojo 

Quick overview of a simple neural network; at its simplest is has at least three layers of neurons where the output of the first layer's neuron, the input layer, is connected as an input to every neuron in the next layer, the hidden layer. The output of the neurons in the hidden layer connects as inputs to every neuron in the final output layer - which gives the outputs from the network The figure below gives an overview; neurons are processing units.

Well, sort of. Neurons as processing units is certainly true for the hidden and the output layers. It is not true though for the input layer; this is literally a layer of inputs with no processing going on. So going back to the first figure of tinkercad microbit neural network and comparing it with the overview of the neural network we can see the three layers.

The input layer is just the two switches.  Hidden layer neurons taks the inputs and processes them (the red abd green microbits in the image. finally, the yellow microbit takes inputs from the 'hidden layer neurons' is the output layer - a single output requires a single neuron in the output layer.

All of this can be found at https://www.tinkercad.com/things/hPV4nU0Asr5-smooth-bojo

Have a play,

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