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But what is a neural network?

This video breaks down neural networks using the example of handwritten digit recognition, explaining neurons, layers, weights, biases, and how the network actually learns.

Network Structure 00:00
  • A neural network has layers: input (784 neurons for 28x28 pixel images), hidden layers, and output (10 neurons for digits 0-9)
  • Each neuron holds a number between 0 and 1 called its "activation"
Weights & Biases 09:10
  • Weights determine how much each connection matters — positive weights amplify, negative ones suppress
  • Bias sets the threshold for when a neuron should activate (e.g. only fire when weighted sum > 10)