Tanh

Essential AI Math Excel Blueprints

The Tanh activation function takes any number and smoothly squeezes it into a range between –1 and 1. It keeps the signal centered around zero, which helps the network learn more efficiently, especially in deeper layers. Like a gentle S‑shaped curve, it allows strong signals to pass through while taming extreme values, making it a popular choice when you want both positive and negative activity in the model.

In comparison, the sigmoid activation function σ(x) squeezes a value into a range between 0 and 1. It also has an S-shaped curve, but it’s centered at y = 0.5, and its most active transition occurs roughly in the x-range of –6 to 6, wider than that of tanh.

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