Video Training →Practical Design Of A Neural Network In C++Step By Step

Neural network Simulator design in C++

What you'll learn
The student will learn how to design the structure of a neural network including its neurons, bias, input layer, hidden layers, output layers and weights
The student will have a clear understanding of how the feed forward mechanism is used to shift inputs from the input layer through the output layer
The student will learn how to calculate the Root Mean Square error, output and hidden gradient, transfer function and the derivatives for a neural network
The student will also carryout back propagation on a neural network after the feed forward and use it for adjusting the weights of the neurons.
The student will learn how to generate training samples

Requirements
Theoritical Understanding of neural network, feed forward and back propagation
Basic knowledge of C++ is required

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