What is a neural network?

02 · See it in action

Follow the steps

1. Choose two inputs, two weights and a bias.
2. Compute the weighted sum.
3. Apply a simple activation such as ReLU.
4. Compare the output with a target and describe the resulting error.

Worked example

x = [2, 3], weights = [0.5, -1], bias = 1
z = 2*0.5 + 3*(-1) + 1 = -1
ReLU(z) = max(0, z) = 0
This is a forward pass, not a complete training algorithm.

Read the example once, then explain each part aloud in your own words. If it includes Python, you can understand the idea first and run the code later in a local Python environment. Code is shown as text; this page does not execute it.

Sign in to save your reading progress.