Recurrent Neural Networks

Recurrent Neural Networks

University

15 Qs

quiz-placeholder

Similar activities

UK Knowledge Test

UK Knowledge Test

University

10 Qs

RM 263 - Research Methods

RM 263 - Research Methods

University

20 Qs

MIDWIFERY AND OBSTETRICAL NURSING

MIDWIFERY AND OBSTETRICAL NURSING

University

20 Qs

BLUETOOTH CONNECTION

BLUETOOTH CONNECTION

8th Grade - University

18 Qs

Business Ethics

Business Ethics

University

10 Qs

BJT AC Analysis Round1

BJT AC Analysis Round1

University

20 Qs

BAC1054 Process Costing

BAC1054 Process Costing

University

15 Qs

QUIZ SECTION 1 DAY 5

QUIZ SECTION 1 DAY 5

7th Grade - University

20 Qs

Recurrent Neural Networks

Recurrent Neural Networks

Assessment

Quiz

Other

University

Practice Problem

Medium

Created by

Shilpa Mahajan

Used 9+ times

FREE Resource

AI

Enhance your content in a minute

Add similar questions
Adjust reading levels
Convert to real-world scenario
Translate activity
More...

15 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the basic architecture of a Recurrent Neural Network (RNN)?

Input layer, hidden layer with random connections, output layer

Input layer, output layer, hidden layer

Input layer, hidden layer without loop connections, output layer

Input layer, hidden layer with loop connections, output layer

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Explain the training process of a Recurrent Neural Network (RNN).

The training process of a Recurrent Neural Network (RNN) involves feeding input sequences into the network, computing the output, comparing it to the actual output, calculating the loss, and then using backpropagation through time (BPTT) to update the weights. This process is repeated for multiple epochs until the model converges.

In RNN training, the loss calculation is not necessary

RNN training requires updating weights only once instead of multiple epochs

The training process of an RNN involves only forward propagation without any backpropagation

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What are some common applications of Recurrent Neural Networks (RNNs)?

Image recognition

Stock market prediction

NLP, speech recognition, time series analysis, language translation

Sentiment analysis

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is Long Short-Term Memory (LSTM) and how does it differ from traditional RNNs?

LSTMs differ from traditional RNNs by having additional gates (input, output, forget) that control the flow of information, enabling them to capture long-term dependencies more effectively.

LSTMs have a fixed sequence length while traditional RNNs do not

LSTMs do not use activation functions like tanh or sigmoid

LSTMs have fewer layers compared to traditional RNNs

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does the vanishing gradient problem affect training in RNNs?

The vanishing gradient problem affects training in RNNs by hindering the ability of the model to effectively learn and capture long-term dependencies.

The vanishing gradient problem in RNNs only affects short-term memory capabilities.

The vanishing gradient problem does not impact the ability of RNNs to learn long-term dependencies.

The vanishing gradient problem in RNNs leads to faster convergence during training.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of the forget gate in an LSTM cell?

To decide what information to discard from the cell state.

To amplify all information in the cell state

To determine the output of the LSTM cell

To randomly select information from the cell state

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does the input gate in an LSTM cell control the flow of information?

By using a linear activation function to determine the input data flow

By using a sigmoid activation function to decide how much of the new input data should be stored in the cell state.

By randomly selecting which input data to keep in the cell state

By ignoring the input data completely

Access all questions and much more by creating a free account

Create resources

Host any resource

Get auto-graded reports

Google

Continue with Google

Email

Continue with Email

Classlink

Continue with Classlink

Clever

Continue with Clever

or continue with

Microsoft

Microsoft

Apple

Apple

Others

Others

Already have an account?