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A single neuron
Write sigmoid(z) and neuron(inputs, weights, bias) which returns the sigmoid of the weighted sum plus the bias. Print the neuron's output, rounded to 4 decimal places, for each input pair.
Learn
An artificial neuron adds up its weighted inputs plus a bias, then squashes the total with an activation function. The sigmoid, 1 รท (1 + e^โz), squashes any number into the range 0 to 1, so the output can be read as a confidence. Big positive totals give nearly 1, big negative ones nearly 0, and a total of 0 gives exactly 0.5.
Your task
Write sigmoid(z) and neuron(inputs, weights, bias) which returns the sigmoid of the weighted sum plus the bias. Print the neuron's output, rounded to 4 decimal places, for each input pair.
Stretch challenge
Show that sigmoid(-z) equals 1 - sigmoid(z) for several z.
Press Run to see what your program prints.
More in this module
Keep going in Coding Grandmaster
A two-layer network
Write forward(x1, x2) for a network with two hidden neurons and one output neuron, using the given weights, and print the output rounded to 3 decimal places for the four input pairs.
Start โ45Teaching a neuron OR
Train a neuron on the OR table, starting from weights 0.1, -0.1 and bias 0, for 1,000 epochs with learning rate lr. Print the four outputs rounded to 2 decimal places.
Start โ46Why XOR needs a hidden layer
Write step(z) and xor_net(a, b) using two hidden neurons, h1 = step(a + b - 0.5) and h2 = step(a + b - 1.5), and the output step(h1 - h2 - 0.5). Print the XOR table, one line per row, like 0 1 -> 1.
Start โPractise the idea
๐ Play Logic Gate Challenge
Predict the output of AND, OR, XOR, NAND and NOR gates from their inputs.
FAQ
A single neuron: common questions
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