APPLICATION OF SUPERVISED LEARNING
DEEP LEARNING
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
|
|
CNN
|
|
|
MLP
|
|
|
Perceptron
|
|
|
RNN
|
Detailed explanation-1: -Ty: Many-to-Many architecture can also be represented in models where input and output layers are of different size, and the most common application of this kind of RNN architecture is seen in Machine Translation.
Detailed explanation-2: -Neural network It is an information system where input data passes through several interconnected nodes to generate an output. Neural machine translation software uses neural networks to work with enormous datasets.
Detailed explanation-3: -RNNs are designed to take sequences of text as inputs or return sequences of text as outputs, or both. They’re called recurrent because the network’s hidden layers have a loop in which the output and cell state from each time step become inputs at the next time step. This recurrence serves as a form of memory.