Day #66 - Maths behind backpropagation

Today it's mathematical learning for neural network fundamentals.

• Derivation of Backpropagation
• Crash Course in Partial Differentiation
• A Step by Step Backpropagation Example

Keynotes

• In Neural Network, Network forward propagates activation to produce output and it back propagates error to determine weight changes
• Partial Derivative - Derivative of one of the variables holding the rest constant
• Backpropagation uses gradient descent method, one needs to calculate the derivative of squared error function with respect to the weights of the network.

Happy Learning!!!