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DeepLearning_GPT3_questions

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Pytanie 41
Which of the following is a step-size adjustment technique used in the stochastic gradient descent algorithm for optimization in deep learning?
Learning rate decay
Adagrad
Momentum
Nesterov momentum
Pytanie 42
Which of the following is a disadvantage of using the gradient descent algorithm for optimization in deep learning?
It does not require a learning rate
It is computationally expensive
It can only be used for convex objective functions
It may converge to a local minimum
Pytanie 43
What is the gradient descent algorithm used for optimization in deep learning?
An algorithm used to compute the gradient of the objective function
An algorithm used to find the minimum value of the objective function
An algorithm used to find the maximum value of the objective function
An algorithm used to find the stationary points of the objective function
Pytanie 44
What is the purpose of the DataLoader class in PyTorch?
To define the computation graph of a neural network model
To initialize the weights of a neural network model
To load the data in mini-batches during training
To preprocess the input data before training
Pytanie 45
Which of the following is true about the backward() method in PyTorch?
It updates the model parameters using the computed gradients
It is used to compute the forward pass of the model
It is used to perform inference on the trained model
It computes the gradients of the loss function with respect to the model parameters
Pytanie 46
What is the purpose of torch.nn.functional in PyTorch?
To provide a set of pre-defined functions for neural network operations
To initialize the weights of a neural network model
To define the computation graph of a neural network model
To compute the gradients of the loss function
Pytanie 47
Which of the following is used for creating custom datasets in PyTorch?
torch.nn
torch.utils.model
torch.optim
torch.utils.data
Pytanie 48
What is the PyTorch module used for optimizing neural network parameters?
torch.utils
torch.optim
torch.tensor
torch.nn
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