Machine Learning and Deep Learning Quiz

What is the purpose of Recurrent Neural Networks (RNNs)?

• To classify images

• To predict the future

• To predict the past

• To analyze static data

What type of data can RNNs analyze?

• Time series data only

• Stock prices only

• Fixed-sized inputs only

• Sequences of arbitrary lengths

What is the function of a memory cell in a neural network?

• Preserves state across time steps

• Calculates outputs instantly

• Ignores previous inputs

• Stores data temporarily

What is the purpose of an encoder and decoder in a neural network?

• To classify images

• To generate random data

• To translate languages

• To confuse the network

How is training done in RNNs?

• No training required

• Manual calculation of gradients

• Backpropagation through time (BPTT)

• Forward pass only

What is the purpose of baseline metrics in machine learning?

• To slow down training

• To confuse researchers

• To measure initial model performance

• To hide model errors

What is the activation function used in a SimpleRNN layer by default?

• Linear

• Sigmoid

• Hyperbolic tangent

• ReLU

What is the purpose of stacking multiple layers of cells in RNNs?

• To complicate the model

• To simplify the model

• To reduce accuracy

• To create a Deep RNN

What is the benefit of forecasting several time steps ahead in RNNs?

• Ignores future predictions

• Reduces model complexity

• Increases accuracy

• Slows down training

How can a model be turned into a sequence-to-sequence model in RNNs?

• By setting return_sequences=False

• By reshaping inputs and outputs

• By using only linear activation functions

• By removing all recurrent layers