Deep Learning Advanced Quiz 8 > Data AI Revolution

Deep Learning Advanced Quiz 8

This quiz is designed to challenge your knowledge and understanding of deep learning concepts, techniques, and applications at an advanced level. Covering 20 multiple-choice questions, this quiz will test you on key areas such as neural network architectures, optimization techniques, model regularization, sequence modeling, and advanced frameworks like GANs and Transformers.

1 / 10

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

Sigmoid

ReLU

Tanh

Softmax

2 / 10

Which technique is commonly used in NLP for word representation?

Pooling

Dropout

Word Embeddings

Batch Normalization

3 / 10

What is the purpose of using skip connections in ResNet?

To add extra parameters

To prevent vanishing gradients

To improve the computational speed

To reduce model size

4 / 10

Which of the following is a type of autoencoder used for unsupervised learning?

CNN

Variational Autoencoder

LSTM

GAN

5 / 10

What does the softmax function do in the output layer of a neural network?

Normalizes outputs to a range between 0 and 1

Calculates gradients

Reduces dimensionality

) Replaces activations with 0 or 1

6 / 10

Which optimization algorithm adapts the learning rate for each parameter?

SGD

RMSprop

Adam

Adagrad

7 / 10

What is the vanishing gradient problem?

Gradients grow exponentially large

Gradients only affect the output layer

Weights are not updated

Gradients disappear when backpropagating

8 / 10

In a convolutional neural network (CNN), what is the purpose of pooling layers?To add non-linearityTo add non-linearity

To add non-linearity

To reduce spatial dimensions

To increase feature map size

To prevent overfitting

9 / 10

What is the primary purpose of the activation function in a neural network?

To introduce non-linearity

To improve the convergence speed

To reduce the number of neurons

To increase model complexity

10 / 10

Which of the following techniques can help prevent overfitting in a neural network?

Increasing batch size

Using dropout

Reducing the number of layers

All of the above

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Deep Learning Advanced Quiz 8

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