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Questions and Answers
What is the fundamental component of all deep learning models?
What is the fundamental component of all deep learning models?
What is the function of weights in an artificial neuron?
What is the function of weights in an artificial neuron?
Which algorithm is used to calculate weight and bias updates in deep learning models?
Which algorithm is used to calculate weight and bias updates in deep learning models?
What is the purpose of the activation function in an artificial neuron?
What is the purpose of the activation function in an artificial neuron?
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Which type of computing has contributed to the popularity of deep learning?
Which type of computing has contributed to the popularity of deep learning?
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What has made it easier to define and train complex architectures in deep learning?
What has made it easier to define and train complex architectures in deep learning?
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In a Convolutional Neural Network (CNN), what is the purpose of the pooling layer?
In a Convolutional Neural Network (CNN), what is the purpose of the pooling layer?
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Which type of layers are always the last few layers in a Convolutional Neural Network (CNN)?
Which type of layers are always the last few layers in a Convolutional Neural Network (CNN)?
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What is the main purpose of the convolution layer in a CNN?
What is the main purpose of the convolution layer in a CNN?
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What does the size of the filters (k×k) represent in a convolution layer?
What does the size of the filters (k×k) represent in a convolution layer?
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In a Convolutional Neural Network (CNN), what does the stride represent in a filter?
In a Convolutional Neural Network (CNN), what does the stride represent in a filter?
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What is the traditional purpose of padding in a convolution layer?
What is the traditional purpose of padding in a convolution layer?
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What is a common task performed by fully connected layers in a CNN?
What is a common task performed by fully connected layers in a CNN?
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What does MLP stand for in reference to neural networks?
What does MLP stand for in reference to neural networks?
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What does M represent in the context of training samples for neural networks?
What does M represent in the context of training samples for neural networks?
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What is one of the main issues associated with dead neurons in neural networks?
What is one of the main issues associated with dead neurons in neural networks?
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