Review Test Quiz

What is the primary purpose of a recurrent neural network (RNN) in natural language processing?

• Image classification

• Handling sequential data

• Speech recognition

• Dimensionality reduction

Which layer type is typically used to extract local features in a CNN?

• Convolutional layer

• Pooling layer

• Fully connected layer

• Activation layer

What is a Generative Adversarial Network (GAN)?

• A network for data analysis

• A type of neural network architecture for generative modelling

• A network for fast data processing

• A network for data encryption

What does the term "transfer learning" mean in the context of deep learning for NLP?

• Moving data between servers

• Learning from one task and applying it to another

• Adjusting learning rates during training

• Parallel processing in neural networks

Which of the following is a widely used and effective machine learning algorithm based on the idea of bagging?

• Decision Tree

• Regression

• Classification

• Random Forest

You observe the following while fitting a linear regression to the data: As you increase the amount of training data, the test error decreases and the training error increases. The train error is quite low (almost what you expect it to), while the test error is much higher than the train error. What do you think is the main reason behind this behaviour? Choose the most probable option.

• High variance

• High model bias

• High estimation bias

• None of the above

refers to a model that can neither model the training data nor generalized to new data.

• Good fitting

• Overfitting

• Underfitting

• All of the above

Imagine a new born starts walking. It will try to find a suitable policy to learn to walk after repeated falling and getting up. Specify what type of machine learning algorithm is best suited to do the same.

• Supervised learning

• Unsupervised learning

• Semi-supervised learning

• Reinforced learning

The maximum degree of any vertex in a simple graph with n vertices is

• n–1

• n+1

• 2n–1

• n

What is the purpose of backpropagation in neural networks?

• Forward pass to make predictions

• Adjusting weights to minimize prediction errors

• Activating neurons in the output layer

• Normalizing input data