Activation Functions
Mathematical equations that determine the output of a neural network.
Description
Activation functions are mathematical equations that determine the output of a neural network. They are attached to each neuron in the network and determine whether it should be activated or not, based on the relevance of the input. Activation functions also help normalize the output of each neuron to a range between 1 and 0 or between -1 and 1.
Examples
- 📈 ReLU (Rectified Linear Unit)
- 🔄 Sigmoid
- 〰️ Tanh (Hyperbolic Tangent)
Applications
Related Terms
Featured
AI PDF Assistant
AI PDF Assistant is an intelligent recommendation tool
Un AI my text
“Where AI Gets Its Human Touch.”
Hailuo AI
AI Video Generator from Text & Image
ChatGPT Atlas
The browser with ChatGPT built in
TurboLearn AI
AI Note Taker & Study Tools
Kimi AI
Kimi AI - K2 chatbot for long-context coding and research
Sora 2
Transform Ideas into Stunning Videos with Sora 2
Genspark AI
Your All-in-One AI Workspace
Animon AI
Create anime videos for free
Abacus AI
The World's First Super Assistant for Professionals and Enterprises
Blackbox AI
Accelerate development with Blackbox AI's multi-model platform
Winston AI
The most trusted AI detector
