b) With backpropagation, the gradient becomes smaller as it works back

1.	b) With backpropagation, the gradient becomes smaller as it works back through the net
Answer» Artificial Neural Network (ANN) can be of two main categories: Feed-FORWARD neural networks and recursive neural networks. They are flexible to many possible VARIATIONS based on – the learning rule, the inference rule and the architecture. Feed forward neural network can be described as per below diagram: Perceptron algorithm is a fundamental computational unit at heart of the Deep learning model. It’s a SUPERVISED learning algorithm for binary classification. There are many packages available for ANNs. In R, some of the packages are nnet, neuralnet, RSNNS, deepnet, darch, caret, RNN, Autoencoder, RcppDL, MXNetR and OTHERS for more specific tasks.

b) With backpropagation, the gradient becomes smaller as it works back through the net

Answer»

Artificial Neural Network (ANN) can be of two main categories: Feed-FORWARD neural networks and recursive neural networks. They are flexible to many possible VARIATIONS based on – the learning rule, the inference rule and the architecture.

Feed forward neural network can be described as per below diagram:

Perceptron algorithm is a fundamental computational unit at heart of the Deep learning model. It’s a SUPERVISED learning algorithm for binary classification.

There are many packages available for ANNs. In R, some of the packages are nnet, neuralnet, RSNNS, deepnet, darch, caret, RNN, Autoencoder, RcppDL, MXNetR and OTHERS for more specific tasks.

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