A Feed-Forward Neural Network is a type of Neural Network architecture where the connections are “fed forwardâ€, i.e. do not form cycles. The term “Feed-Forward†is also used when you input something at the input layer and it travels from input to hidden and from hidden to the output layer.
Backpropagation is a training algorithm consisting of 2 steps:
<> Feed-Forward the values.
<> Calculate the error and propagate it back to the earlier layers.
So to be precise, forward-propagation is part of the backpropagation algorithm but comes before back-propagating.
Posted Date:- 2022-02-15 12:04:03
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Explain the different Layers of CNN.
List a few advantages of TensorFlow?
Name a few deep learning frameworks
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What is a Multi-Layer-Perceptron
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What are the benefits of mini-batch gradient descent?
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Explain Learning of a Perceptron.
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What is the role of weights and bias?
What is Perceptron? And How does it Work?
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Which deep learning algorithm is the best for face detection?
Explain Stochastic Gradient Descent. How is it different from Batch Gradient Descent ?
Explain Batch Gradient Descent.
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Explain transfer learning in the context of deep learning.
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Explain Forward and Back Propagation in the context of deep learning.
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What do you mean by end-to-end learning?
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Explain what a deep neural network is.
What are the disadvantages of neural networks?
What are the advantages of neural networks?
What are the applications of deep learning?
Differentiate between AI, Machine Learning and Deep Learning.