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Quiz on LSTM in Deep Learning

Quiz on LSTM in Deep Learning

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Question 1 of 10

1. Question

What does LSTM stand for?

Long Short-Term Memory
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Large Scale Time Model
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Local Sequential Time Machine
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Linear Sequence Training Model
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Question 2 of 10

2. Question

What problem does LSTM solve in traditional RNNs?

Overfitting
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Low training speed
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Vanishing gradient problem
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Data duplication
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Question 3 of 10

3. Question

Which of the following is NOT a gate used in LSTM?

Input Gate
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Update Gate
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Forget Gate
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Output Gate
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Question 4 of 10

4. Question

Which activation function is commonly used in LSTM gates?

ReLU
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Sigmoid
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Softmax
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Tanh
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Question 5 of 10

5. Question

What is the purpose of the Forget Gate in an LSTM cell?

To store output from previous steps
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To decide what information to discard
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To collect final predictions
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To increase training speed
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Question 6 of 10

6. Question

What kind of data is LSTM mainly used for?

Random data
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Tabular data
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Sequential data
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Image data only
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Question 7 of 10

7. Question

Which is an example of sequential data suitable for LSTM?

Barcodes
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Customer ID numbers
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Time series data
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Unique product codes
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Question 8 of 10

8. Question

In LSTM, which gate controls what new information is added to memory?

Output Gate
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Forget Gate
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Input Gate
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Memory Gate
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Question 9 of 10

9. Question

Why is LSTM better than traditional RNNs for long sequences?

It trains faster
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It requires fewer data
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It remembers information for longer durations
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It uses fewer parameters
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Question 10 of 10

10. Question

Which of the following is a common use-case of LSTM?

Sorting numbers
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Predicting random values
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Sentiment analysis
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Static image classification
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