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RNN model Used for sequential data modeling. (A-B-C-D-?, ? is probably E considered of ahead) Special types of fully connected neural network. Connection weights are shared by all layers. Encoder It recieves all the words sequentially, and at the end, it compresses all of these word into A Vector which is called a CONTEXT VECTOR. context vector It recieves all the words and then passed the hidde..

Feed Forward Neural Network(FFNN) An extension of the logistic regression algorithm. FFNN are stacking multiple hidden layers (any layers that's not the input or output layer) followed by non linear activation, such as the sigmoid or softmax activations. FFNN are only made of fully connected layers, where each neuron in one layer is connected to all the neurons in the previous layer. y=f*(x) y :..