Tag: ai notes
-
Activation Functions
The perceptron algorithm together with the Heaviside function can only be used for binary classification. In order to use the algorithm for other types of classifications, there are several other functions which can be used. Non-linear activation functions can be used in order to separate data that is not linearly seperable. Popular activation functions:
-
Heaviside Step Function
Named after the English mathematician and physicist Oliver Heaviside, the Heaviside step function was used in Rosenblatt’s perceptron. It is a piecewise function and is mathematically defined as The Heaviside step function essentially gives the perceptron algorithm its binary decision-making property.
-
Mathematics of Perceptrons
The perceptron algorithm is a basic artificial neuron and is considered to be a building block of neural networks. It takes inputs, applies weights and produces output using an activation function. A supervised learning algorithm, it is a binary classifier, separating data points using a linear combination of the input variables. The algorithm consists of…
Learn.Do.Rinse.Repeat. 