Single Artificial Neuron

It's a webpage that presents some animated charts for basic examples of Perceptron, Adaline and Gradient Descent procedure.

For Perceptron and Adaline examples, the initial values of weights (W) and bias are randomly generated and updated according to the selected algorithm.

Perceptron

This page presents a visual example of a single artificial neuron fiting over the logical port 'AND'. One can check how the Perceptron works to separate the output in "0" and "1".

Adaline

This page presents a visual example of a single artificial neuron fiting over the logical port 'AND'. One can check how the Perceptron works to separate the output in "0" and "1".

Gradient

Gradient Descent is usually applied to guide the adjustment of the synaptic weights in artificial neural networks.

This page presents a visual example on how Gradient Descent works in finding minimal values to f(x) = x4 - 3x3 + 2. You can choice a start point by hitting at the graph or clicking in 'Random x' button.

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The parameters at 'Options' section may be used to control the behavior of each example.

External libs

• jQuery
• Plotly