Deep Learning Expert Quiz 10 > Data AI Revolution

Deep Learning Expert Quiz 10

Dive into the depths of neural networks, backpropagation, and cutting-edge architectures with this challenging deep learning quiz. This quiz is crafted for those who are already familiar with the basics and intermediate concepts of deep learning and are ready to test their understanding of advanced topics.

1 / 10

Which regularization technique is NOT commonly used in deep reinforcement learning?

Dropout

L2 regularization

Entropy regularization

Target network stabilization

2 / 10

What is the role of attention heads in multi-head attention in Transformer models?

To improve the model’s interpretability

To capture different relationships in the input sequence

To reduce model complexity

To increase model robustness to noise

3 / 10

Which of the following is true for Residual Networks (ResNets) with very deep architectures?

They perform better with high dropout rates.

They often experience vanishing gradients.

They leverage skip connections to stabilize training.

They do not require normalization.

4 / 10

Which of the following metrics is typically optimized in a reinforcement learning setup with policy gradients?

Q-value

Mean squared error

Cumulative reward

Kullback-Leibler divergence

5 / 10

Which type of RNN is most effective in handling very long sequences?

Basic RNN

Bidirectional RNN

Long Short-Term Memory (LSTM)

Transformer model

6 / 10

What is the purpose of gradient penalty in Wasserstein GANs (WGAN-GP)?

To prevent mode collapse

To enforce the Lipschitz constraint

To improve image resolution

To reduce the number of training steps

7 / 10

Which optimization algorithm uses both first and second moments of the gradients?

SGD with momentum

AdaGrad

RMSprop

Adam

8 / 10

In Transformer models, the "Scaled Dot-Product Attention" uses a scaling factor. Why is this scaling factor applied?

To prevent gradients from vanishing

To reduce the variance of the dot products

To improve computational efficiency

To increase the complexity of the model

9 / 10

Which approach is used to improve the generalization of GANs when training on diverse datasets?

Data augmentation with noise injection

Spectral normalization in discriminator

Using Batch Normalization in both generator and discriminator

Applying dropout in the generator

10 / 10

Which activation function is preferred in deep networks to prevent vanishing gradients?

Sigmoid

ReLU

Tanh

Softmax

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Deep Learning Expert Quiz 10

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