solved questions quizes library in Deep Learning

Assume that your machine has a large enough RAM dedicated to training neural networks. Compared to using stochastic gradient descent for your optimization, choosing a batch size that fits your RAM will lead to::

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2022-06-14

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Which of the following methods DOES NOT prevent a model from overfitting to the training set?

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2022-06-14

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In which neural net architecture, does weight sharing occur?

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What consist of Boltzmann machine?

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2022-06-14

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Which, if any, of the following propositions is true about fully-connected neural networks (FCNN)?

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Sentiment analysis using Deep Learning is a many-to one prediction task

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2022-06-14

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In CNN, having max pooling always decrease the parameters?

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Which of the following would have a constant input in each epoch of training a Deep Learning model?

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In a simple MLP model with 8 neurons in the input layer, 5 neurons in the hidden layer and 1 neuron in the output layer. What is the size of the weight matrices between hidden output layer and input hidden layer?

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2022-06-14

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Assume a simple MLP model with 3 neurons and inputs= 1,2,3. The weights to the input neurons are 4,5 and 6 respectively. Assume the activation function is a linear constant value of 3. What will be the output ?

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In which of the following applications can we use deep learning to solve the problem?

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2022-06-14

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The number of nodes in the input layer is 10 and the hidden layer is 5. The maximum number of connections from the input layer to the hidden layer are

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2022-06-14

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Which of the following functions can be used as an activation function in the output layer if we wish to predict the probabilities of n classes (p1, p2..pk) such that sum of p over all n equals to 1?

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Deep Learning questions

Deep Learning MCQ Quiz (Multiple Choice Questions And Answers)

Assume that your machine has a large enough RAM dedicated to training neural networks. Compared to using stochastic gradient descent for your optimization, choosing a batch size that fits your RAM will lead to::

Which of the following methods DOES NOT prevent a model from overfitting to the training set?

In which neural net architecture, does weight sharing occur?

What consist of Boltzmann machine?

Which, if any, of the following propositions is true about fully-connected neural networks (FCNN)?

Sentiment analysis using Deep Learning is a many-to one prediction task

In CNN, having max pooling always decrease the parameters?

Which of the following would have a constant input in each epoch of training a Deep Learning model?

In a simple MLP model with 8 neurons in the input layer, 5 neurons in the hidden layer and 1 neuron in the output layer. What is the size of the weight matrices between hidden output layer and input hidden layer?

Assume a simple MLP model with 3 neurons and inputs= 1,2,3. The weights to the input neurons are 4,5 and 6 respectively. Assume the activation function is a linear constant value of 3. What will be the output ?

In which of the following applications can we use deep learning to solve the problem?

The number of nodes in the input layer is 10 and the hidden layer is 5. The maximum number of connections from the input layer to the hidden layer are

Which of the following functions can be used as an activation function in the output layer if we wish to predict the probabilities of n classes (p1, p2..pk) such that sum of p over all n equals to 1?