Long Short-Term Memory Networks QUIZ - MCQ QUESTIONS AND ANSWERS

Question: 1

What is the primary purpose of an LSTM network in deep learning?

Question: 2

What problem does the vanishing gradient problem address in traditional RNNs?

Question: 3

In the architecture of an LSTM cell, which component is responsible for selectively updating its memory and controlling the flow of information?

Question: 4

What is the primary function of the MinMaxScaler in LSTM data preprocessing?

Question: 5

What is the primary use of Long Short-Term Memory (LSTM) networks?

Question: 6

What problem do Long Short-Term Memory (LSTM) networks aim to address in traditional recurrent neural networks (RNNs)?

Question: 7

How do LSTM networks differ from traditional Recurrent Neural Networks (RNNs) regarding handling long-term dependencies?

Question: 8

What is the role of the "forget gate" in an LSTM cell?

Question: 9

In the context of LSTM implementation, what is the purpose of the "MinMaxScaler" from scikit-learn?

Question: 10

What is the key advantage of using LSTM networks over traditional Recurrent Neural Networks (RNNs)?

Question: 11

Which advanced LSTM technique involves two LSTMs, one processing input in a forward trend and the other in a backward trend?

Question: 12

Which advanced LSTM technique involves the use of multiple hidden LSTM layers with various memory cells?

Question: 13

What is LSTM short for?

Question: 14

Which problem in traditional RNNs do LSTMs aim to overcome?

Question: 15

What is the primary advantage of LSTM networks over traditional RNNs?

Question: 16

Which component in an LSTM unit is responsible for regulating information flow into and out of the cell?

Question: 17

How many gates are there in a standard LSTM unit?

Question: 18

Which gate in an LSTM unit determines what information to discard from the cell state?

Question: 19

In an LSTM unit, what is the purpose of the input gate?

Question: 20

What type of activation function is commonly used in LSTM gates?

Question: 21

In an LSTM network, what is the purpose of the output gate?

Question: 22

Which of the following is true about LSTM networks?

Question: 23

In which domain or type of data are LSTM networks particularly effective?

Question: 24

What problem do LSTM networks address in traditional Recurrent Neural Networks (RNNs)?

Question: 25

Which component of the LSTM architecture is responsible for selectively updating its memory and controlling the flow of information?

Question: 26

What is the primary role of the forget gate in an LSTM cell?

Question: 27

What is the primary function of the "MinMaxScaler" in LSTM data preprocessing?

Question: 28

Which part of an LSTM cell is responsible for maintaining long-term memory?

Question: 29

In an LSTM network, what happens in the "training" phase?

Question: 30

In the context of deep learning, what problem does the vanishing gradient problem pose for traditional RNNs?