Implement the Sigmoid Function — easy Neural Networks problem | Incognition

Implement the Sigmoid Function

10 pts · 10 coins

Neural NetworksEasy

Implement the Sigmoid Function

The sigmoid function squashes any real number into the range (0, 1) — it's the classic activation function that turns a raw score into something that looks like a probability.

Formula: sigmoid(x) = 1 / (1 + e^-x)

Task: write a function sigmoid(x) that takes a single number x and returns sigmoid(x), rounded to 4 decimal places.

Use math.exp for e^x.
Large positive or negative inputs should still return a value strictly between 0 and 1.

Examples

x = 0

returns 0.5

x = 2

returns 0.8808

Hints

solution.py

1import math
2
3def sigmoid(x):
4    # your code here
5    pass
6