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Sequence Models Interview Questions and Answers
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Questions
Sequence Models
0
votes
Q: Recurrent Networks work best for Speech Recognition.
answered
Feb 5, 2022
in
Sequence Models
by
sharadyadav1986
speech-recognition
sequence-model
0
votes
Q: GPU stands for __________.
answered
Feb 5, 2022
in
Sequence Models
by
sharadyadav1986
gpu
sequence-model
0
votes
Q: What is the entity that is carried from one timestep to next in RNN?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
timestep-rnn
0
votes
Q: What is meant by sequence data?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
sequence-data
0
votes
Q: Which of the following considers the information from previous timestep, current ones, as well as future timesteps?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
timestep
0
votes
Q: Which of the following gates in LSTM decides on keeping relevant features from the current input?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
lstm-feature
0
votes
Q: Which of the following gates in LSTM decides on eliminating irrelevant features from previous information?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
lstm-feature
0
votes
Q: In the case of LSTM, which of the following is used to compute the output of a cell?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
lstm
0
votes
Q: Which of the following is the component of GRU?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
gru-component
0
votes
Q: The reason feed forward network cannot be used on sequence data is _____________.
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
feed-network
0
votes
Q: Which of the following is not the feature of GRU?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
gru-features
0
votes
Q: LSTM has a large number of parameters to learn when compared to basic RNN.
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
lstm-parameter
0
votes
Q: GRU has more parameters to learn when compared to LSTM.
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
learn-parameter
0
votes
Q: Which of the following is not a feature of LSTM?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
lstm-feature
0
votes
Q: Which of the following is an additional feature of LSTM when compared to basic RNN?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
lstm-features
0
votes
Q: Which of the following gates (in LSTM) decides on keeping relevant features from the current input?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
lstm
0
votes
Q: In the case of LSTM, which of the following is used to compute the output of a cell?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
lstm
0
votes
Q: In which of the following, the vanishing gradient problem is profound?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
gradient-problem
0
votes
Q: The basic RNN fails when _______________________.
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
rnn-fails
0
votes
Q: Which of the following is not an example of sequential data?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
sequential-data
0
votes
Q: Which of the following holds the memory in RNNs?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
rnn-memory
0
votes
Q: Back propagation through time is computed as ______________.
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
back-propogation
0
votes
Q: Error function in RNN is computed as _________________.
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
error-function
0
votes
Q: Which of the following are the applications of RNN?
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
rnn-applications
0
votes
Q: Feedforward network cannot be used on sequence data because ____________.
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
feedforward-network
0
votes
Q: The main drawback of basic RNN is __________.
answered
Feb 4, 2022
in
Sequence Models
by
sharadyadav1986
rnn-drawback
0
votes
Q: Autoencoders cannot be used for Dimensionality Reduction.
answered
Jul 18, 2020
in
Sequence Models
by
Hodge
#deeplearning
autoencoders
0
votes
Q: How do RNTS interpret words?
answered
Jul 18, 2020
in
Sequence Models
by
Hodge
#deeplearning
rnts-work
0
votes
Q: Autoencoders are trained using _____________________.
answered
Jul 18, 2020
in
Sequence Models
by
Hodge
#deeplearning
0
votes
Q: The rate at which cost changes with respect to weight or bias is called __________________.
answered
Jul 18, 2020
in
Sequence Models
by
Hodge
#deeplearning
bias-weight
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