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Meeting 1Forward propagation

How a neural network moves information

If you missed Meeting 1 or want additional review, use this lesson to understand what a neuron receives, what a connection changes, and how values move forward through layers.

Start the guided tutorialSix editable stages
01

Watch the visual introduction

Use 3Blue1Brown's handwritten-digit example through 13:32. Stop before the compact vector and matrix notation begins.

Open “But what is a neural network?” ↗
02

Walk through five networks

Open the playground and change presets in this order:

  1. 1 → 1Follow one input across one weighted connection.
  2. 2 → 1See how a neuron combines more than one input.
  3. 1 → 2 → 1Introduce a hidden layer and two intermediate values.
  4. 2 → 2 → 1Compare several weighted paths through the same layer.
  5. 3 → 3 → 2Finish with multiple inputs, hidden neurons, and outputs.
Open Neural Network Playground →
03

Try changing one thing

Choose one input, connection, or node. Predict which later values will change, make one edit, and compare your prediction with the result. Then repeat with a different part when you are ready.