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In this write up a technical explanation and functioning of a fully connected neural network which involves bi direction flow, first a forward direction knows as Feed forward and a backward direction known as back propagation.

Take the below example of a fully connected neural network which has two inputs, one hidden layer with 2 neurons and an output layer where 2 neurons represent the two outputs so it can be deemed as a binary class classification.

Hidden layer consists of a summation and an activation function to it, activation functions are used to introduce non linearity other than acting…

Saurabh Kirar

Deep learning architect| Lifelong Learner|

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