Machine Learning & AI

Basic

ReLU Activation

Rectified Linear Unit: outputs the input if positive, else zero.

Formula

f(x) = \max(0, x)

Variables

xInput value

Example

f(-3)=0, f(5)=5

Did You Know?

ReLU is astonishingly simple yet enabled the deep-learning boom by avoiding vanishing gradients.

activation deep learning

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More in Machine Learning & AI

Linear Regression Model

Predicts a continuous value as a weighted sum of input features plus a bias.

Gradient Descent Update

Iteratively moves parameters in the direction that most reduces the loss.

Leaky ReLU

A ReLU variant that lets a small gradient flow for negative inputs.

Tanh Activation

Squashes input to the range (-1, 1); zero-centred activation.

Softmax

Turns a vector of scores into a probability distribution that sums to 1.

Binary Cross-Entropy

Loss for binary classification comparing predicted probability to the true label.