Multilayer Perceptron

• History

Laws of Association

• Contiguity

• Frequency

• Similarity

• Contrast

Biological Neuron

• Cell Body

• Dendrites

• Axon

• Neural Impulse

• Terminal Branches of Axon

• Myelin Sheath

Authors

• McCulloch and Pitts, 1943

• Frank Rosenblatt

Activation Function

• Sigmoid

• Hyperbolic

• Rational

Gradient Descent

Gradient descent is a first-order iterative optimization algorithm. To find a local minimum of a function using gradient descent, one takes steps proportional to the negative of the gradient (or of the approximate gradient) of the function at the current point. If instead one takes steps proportional to the positive of the gradient, one approaches a local maximum of that function; the procedure is then known as gradient ascent. Wikipedia

Training Neuron

• With Mathematics

• With Code

Training Neural Network

The backward propagation of errors or backpropagation, is a common method of training artificial neural networks and used in conjunction with an optimization method such as gradient descent. Wikipedia

• With Mathematics

• With Code

Radial Basis Function