Data Science and Machine Learning (Theory and Projects) A to Z - Project I_ Book Writer: Modelling RNN Model in TensorFl

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10 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of converting sequences to input-target pairs?
To prepare data for training by creating shifted sequences
To increase the dataset size
To reduce the complexity of the model
To enhance the accuracy of predictions
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is it important to shuffle the dataset before training?
To increase the size of the dataset
To reduce bias from temporal or sequential order
To ensure the data is in chronological order
To make the model training faster
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does the embedding dimension represent in the context of dense vectors?
The number of layers in the model
The size of the input data
The number of coordinates in the feature vector
The total number of characters in the vocabulary
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is NOT a type of recurrent unit mentioned?
Convolutional Unit
Simple Recurrent Unit
GRU
LSTM
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the role of the embedding layer in the model?
To define the loss function
To shuffle the dataset
To compile the model
To convert integer indices to dense vectors
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does setting 'return sequences' to true in a GRU layer do?
It increases the batch size
It resets the state after each batch
It returns the output for each time step
It returns the final output only
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of the dense layer in the model?
To reduce the dimensionality of the input
To provide an output for each character in the vocabulary
To shuffle the input data
To compile the model
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