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Lesson 1 of 5
Neural network basics
Watch, read the card, then practise. Neurons and layers · Activation functions
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Practise this topicNeurons and layers
A neuron multiplies each input by a weight, adds them up with a bias, then applies an activation. Layers are many neurons side by side.
Remember: Weights and biases are what training learns.
Activation functions
Activation functions add curves, so stacked layers can learn more than a straight line.
Remember: No activation = the whole network is just one linear model.
Try the example in Code Lab
inputs, neurons = 4, 3 print(inputs * neurons + neurons)