34 + Interview Questions in Deep Learning in Test and Papers Page 1 InterviewSolution

1.	The measure of Difference between two probability distributions is know as ________________________.
Answer» The MEASURE of Difference between two probability distributions is KNOW as ________________________. Choose the CORRECT option from below options (1)Probability Difference (2)Cost (3)KL Divergence (4)Error Answer:- (3)KL Divergence

Discussion

2.	_______________ is a recommended Model for Pattern Recognition in Unlabeled Data.
Answer» _______________ is a recommended MODEL for Pattern Recognition in Unlabeled Data. Choose the correct option from below options (1)CNN (2)Shallow Neural NETWORKS (3)Autoencoders (4)RNN Answer:- (3)Autoencoders

Discussion

3.	Recurrent Networks work best for Speech Recognition.
Answer» RECURRENT Networks WORK best for Speech Recognition. Choose the correct option from below OPTIONS (1)True (2)False Answer:-(1)True

Discussion

4.	GPU stands for __________.
Answer» GPU stands for __________. Choose the correct option from below OPTIONS (1)Graphics Processing Unit (2)GRADIENT Processing Unit (3)GENERAL Processing Unit (4)Good Processing Unit. Answer:- (1)Graphics Processing Unit

Discussion

5.	________________ works best for Image Data.
Answer» ________________ works best for Image Data. Choose the CORRECT option from below OPTIONS (1)AUTOENCODERS (2)Single Layer Perceptrons (3)Convolution Networks (4)RANDOM Forest Answer:- (3)Convolution Networks

Discussion

6.	Neural Networks Algorithms are inspired from the structure and functioning of the Human Biological Neuron.
Answer» NEURAL Networks Algorithms are inspired from the structure and FUNCTIONING of the Human Biological Neuron. Choose the CORRECT option from below options (1)False (2)True Answer:- True

Discussion

7.	In a Neural Network, all the edges and nodes have the same Weight and Bias values.
Answer» In a Neural NETWORK, all the edges and NODES have the same WEIGHT and BIAS values. Choose the correct OPTION from below options (1)True (2)False Answer:- False

Discussion

8.	What is the method to overcome the Decay of Information through time in RNN known as?
Answer» What is the method to overcome the Decay of INFORMATION through time in RNN known as? Choose the CORRECT option from below options (1)Back PROPAGATION (2)Gradient Descent (3)ACTIVATION (4)GATING Answer:- (4)Gating

Discussion

9.	Process of improving the accuracy of a Neural Network is called _______________.
Answer» Process of improving the accuracy of a NEURAL Network is called _______________. Choose the correct option from below options (1)Forward Propagation (2)CROSS Validation (3)Random Walk (4)TRAINING Answer:- (4)Training

Discussion

10.	Data Collected from Survey results is an example of ___________________.
Answer» DATA Collected from Survey results is an example of ___________________. Choose the correct option from below options (1)Data (2)INFORMATION (3)Structured Data (4)Unstructured Data Answer:- (3)Structured Data

Discussion

11.	A Shallow Neural Network has only one hidden layer between Input and Output layers.
Answer» A Shallow Neural Network has only one HIDDEN layer between Input and OUTPUT layers. Choose the correct OPTION from below options (1)FALSE (2)True Answer:- True

Discussion

12.	Support Vector Machines, Naive Bayes and Logistic Regression are used for solving
Answer» SUPPORT Vector Machines, Naive BAYES and Logistic REGRESSION are used for solving ___________________ problems. Choose the correct OPTION from below options (1)Clustering (2)Classification (3)Regression (4)Time Series Answer:- (2)Classification

Discussion

13.	What does LSTM stand for?
Answer» What does LSTM STAND for? Choose the correct option from below options (1)Long Short Term Memory (2)LEAST Squares Term Memory (3)Least Square Time Mean (4)Long Short Threshold Memory Answer:-(1)Long Short Term Memory

Discussion

14.	All the Visible Layers in a Restricted Boltzmannn Machine are connected to each other.
Answer» All the Visible Layers in a Restricted Boltzmannn MACHINE are connected to each other. Choose the correct OPTION from below options (1)True (2)FALSE Answer:- (2)False

Discussion

15.	All the neurons in a convolution layer have different Weights and Biases.
Answer» All the neurons in a convolution layer have DIFFERENT Weights and Biases. Choose the correct option from below OPTIONS (1)True (2)False Answer:- (2)False

Discussion

16.	Recurrent Neural Networks are best suited for Text Processing.
Answer» Recurrent NEURAL NETWORKS are BEST suited for Text Processing. Choose the correct option from below OPTIONS (1)True (2)False Answer:-(1)True

Discussion

17.	Autoencoders cannot be used for Dimensionality Reduction.
Answer» Autoencoders cannot be used for Dimensionality Reduction. Choose the CORRECT OPTION from below OPTIONS (1)FALSE (2)True Answer:-(1)False

Discussion

18.	What is the difference between the actual output and generated output known as?
Answer» What is the DIFFERENCE between the actual OUTPUT and generated output known as? Choose the correct OPTION from below options (1)Output Modulus (2)Accuracy (3)Cost (4)Output Difference Answer:-(3)Cost

Discussion

19.	Gradient at a given layer is the product of all gradients at the previous layers.
Answer» Gradient at a GIVEN LAYER is the PRODUCT of all gradients at the previous layers. Choose the correct OPTION from below OPTIONS (1)False (2)True Answer:- True

Discussion

20.	Prediction Accuracy of a Neural Network depends on _______________ and ______________.
Answer» Prediction Accuracy of a Neural Network DEPENDS on _______________ and ______________. CHOOSE the correct option from below options (1)Input and Output (2)Weight and BIAS (3)LINEAR and Logistic Function (4)Activation and Threshold Answer:-(2)Weight and Bias

Discussion

21.	Restricted Boltzmann Machine expects the data to be labeled for Training.
Answer» RESTRICTED Boltzmann Machine EXPECTS the data to be LABELED for Training. Choose the correct option from below options (1)False (2)True Answer:- (1)False

Discussion

22.	Recurrent Network can input Sequence of Data Points and Produce a Sequence of Output.
Answer» Recurrent Network can input SEQUENCE of Data Points and PRODUCE a Sequence of Output. Choose the CORRECT OPTION from below options (1)False (2)True Answer:- (2)True

Discussion

23.	_____________________ is a Neural Nets way of classifying inputs.
Answer» _____________________ is a Neural Nets WAY of classifying inputs. Choose the correct option from below options (1)Learning (2)Forward Propagation (3)ACTIVATION (4)Classification Answer:- (2)Forward Propagation

Discussion

24.	A Deep Belief Network is a stack of Restricted Boltzmann Machines.
Answer» A DEEP BELIEF Network is a stack of Restricted Boltzmann Machines. Choose the correct OPTION from below OPTIONS (1)FALSE (2)True Answer:-(2)True

Discussion

25.	Name the component of a Neural Network where the true value of the input is not observed.
Answer» NAME the component of a Neural NETWORK where the true VALUE of the input is not observed. Choose the CORRECT option from below options (1)Hidden Layer (2)Gradient Descent (3)Activation Function (4)Output Layer Answer:- (1)Hidden Layer

Discussion

26.	Why is the Pooling Layer used in a Convolution Neural Network?
Answer» Why is the Pooling LAYER used in a Convolution Neural NETWORK? CHOOSE the correct option from below options (1)They are of no use in CNN. (2)Dimension REDUCTION (3)Object RECOGNITION (4)Image Sensing Answer:- (2)Dimension Reduction

Discussion

27.	What is the best Neural Network Model for Temporal Data?
Answer» What is the best Neural Network Model for TEMPORAL Data? Choose the CORRECT option from below options (1)Recurrent Neural Network (2)Convolution Neural NETWORKS (3)Temporal Neural Networks (4)Multi Layer Perceptrons Answer:- (1)Recurrent Neural Network

Discussion

28.	RELU stands for ______________________________.
Answer» RELU stands for ______________________________. Choose the CORRECT OPTION from below options (1)Rectified Linear UNIT (2)Rectified LAGRANGIAN Unit (3)Regressive Linear Unit (4)Regressive Lagrangian Unit Answer:- (1)Rectified Linear Unit

Discussion

29.	What are the two layers of a Restricted Boltzmann Machine called?
Answer» What are the two layers of a RESTRICTED Boltzmann Machine called? Choose the correct option from below OPTIONS (1)Input and Output Layers (2)Recurrent and CONVOLUTION Layers (3)Activation and Threshold Layers (4)Hidden and Visible Layers Answer:- (4)Hidden and Visible Layers

Discussion

30.	How do RNTS interpret words?
Answer» How do RNTS interpret words? Choose the correct option from below options (1)One Hot Encoding (2)LOWER Case Versions (3)WORD FREQUENCIES (4)Vector Representations Answer:-(4)Vector Representations

Discussion

31.	Autoencoders are trained using _____________________.
Answer» Autoencoders are trained using _____________________. Choose the correct option from below OPTIONS (1)Feed Forward (2)RECONSTRUCTION (3)Back PROPAGATION (4)They do not require Training Answer:- (3)Back Propagation

Discussion

32.	The rate at which cost changes with respect to weight or bias is called __________________.
Answer» The rate at which cost changes with respect to weight or bias is called __________________. CHOOSE the correct option from below OPTIONS (1)Derivative (2)Gradient (3)Rate of Change (4)Loss Answer:- (2)Gradient

Discussion

33.	A _________________ matches or surpasses the output of an individual neuron to a visual stimuli.
Answer» A _________________ matches or surpasses the output of an INDIVIDUAL neuron to a visual stimuli. Choose the correct option from below options (1)Max POOLING (2)Gradient (3)Cost (4)CONVOLUTION Answer:- (4)Convolution

Discussion

34.	Deep Learning Questions Answers
Answer» Below are the different Deep Leaning Questions and answer are followed by the questions (1)What is the difference between the actual output and generated output known as? Output Modulus Accuracy Cost Output Difference Answer:-Cost (2)Recurrent Neural Networks are best suited for Text Processing. True False Answer:-True (3)Prediction Accuracy of a Neural Network depends on _______________ and ______________. Input and Output Weight and Bias Linear and Logistic Function Activation and Threshold Answer:-Weight and Bias (4)Recurrent Networks work best for Speech Recognition. True False Answer:-True (5)GPU stands for __________. Graphics Processing Unit GRADIENT Processing Unit General Processing Unit Good Processing Unit. Answer:- Graphics Processing Unit (6)Gradient at a given layer is the product of all gradients at the PREVIOUS layers. False True Answer:- True (7)_____________________ is a Neural Nets way of classifying inputs. Learning Forward Propagation Activation Classification Answer:- Forward Propagation (8)Name the component of a Neural Network where the true value of the input is not observed. Hidden Layer Gradient Descent Activation Function Output Layer Answer:- Hidden Layer (9)________________ works best for Image Data. AutoEncoders Single Layer Perceptrons Convolution Networks Random Forest Answer:- Convolution Networks (10)Neural Networks Algorithms are inspired from the structure and functioning of the Human Biological NEURON. False True Answer:- True (11)In a Neural Network, all the edges and nodes have the same Weight and Bias values. True False Answer:- False (12)_______________ is a recommended Model for Pattern Recognition in Unlabeled Data. CNN Shallow Neural Networks Autoencoders RNN Answer:- Autoencoders (13)Process of improving the accuracy of a Neural Network is called _______________. Forward Propagation Cross Validation Random Walk Training Answer:- Training (14)Data Collected from Survey results is an example of ___________________. Data Information Structured Data Unstructured Data Answer:- Structured Data (15)A Shallow Neural Network has only one hidden layer between Input and Output layers. False True Answer:- True (16)Support Vector Machines, Naive Bayes and Logistic Regression are used for solving ___________________ problems. Clustering Classification Regression Time Series Answer:- Classification (17)The rate at which cost changes with respect to weight or bias is called __________________. Derivative Gradient Rate of Change Loss (18)What does LSTM stand for? Long Short Term Memory Least Squares Term Memory Least Square Time Mean Long Short Threshold Memory Answer:-Long Short Term Memory (19)All the Visible Layers in a Restricted Boltzmannn Machine are connected to each other. True False Answer:- False (20)All the neurons in a convolution layer have different Weights and Biases. True False Answer:- False (21)What is the method to overcome the DECAY of Information through time in RNN known as? Back Propagation Gradient Descent Activation Gating Answer:- Gating (22)Recurrent Network can input Sequence of Data Points and Produce a Sequence of Output. False True Answer:- True (23)A Deep Belief Network is a stack of Restricted Boltzmann Machines. False True Answer:-True (24)Restricted Boltzmann Machine expects the data to be labeled for Training. False True Answer:- False (25)What is the best Neural Network Model for Temporal Data? Recurrent Neural Network Convolution Neural Networks Temporal Neural Networks Multi Layer Perceptrons Answer:- Recurrent Neural Network (26)RELU stands for ______________________________. Rectified Linear Unit Rectified Lagrangian Unit Regressive Linear Unit Regressive Lagrangian Unit Answer:- Rectified Linear Unit (27)Why is the Pooling Layer used in a Convolution Neural Network? They are of no use in CNN. Dimension Reduction Object Recognition Image Sensing Answer:- Dimension Reduction (28)What are the two layers of a Restricted Boltzmann Machine called? Input and Output Layers Recurrent and Convolution Layers Activation and Threshold Layers Hidden and Visible Layers Answer:- Hidden and Visible Layers (29)The measure of Difference between two probability distributions is know as ________________________. Probability Difference Cost KL Divergence Error Answer:- KL Divergence (30)A _________________ matches or surpasses the output of an individual neuron to a visual stimuli. Max Pooling Gradient Cost Convolution Answer:- Convolution (31)The rate at which cost changes with respect to weight or bias is called __________________. Derivative Gradient Rate of Change Loss Answer:- Gradient (32)Autoencoders are trained using _____________________. Feed Forward Reconstruction Back Propagation They do not require Training Answer:- Back Propagation (33)How do RNTS interpret words? One Hot Encoding Lower Case Versions Word Frequencies Vector Representations Answer:-Vector Representations (34)De-noising and Contractive are examples of __________________. Shallow Neural Networks Autoencoders Convolution Neural Networks Recurrent Neural Networks Answer:-Autoencoders (35)Autoencoders cannot be used for Dimensionality Reduction. False True Answer:-False

Discussion

Explore topic-wise InterviewSolutions in .

The measure of Difference between two probability distributions is know as ________________________.

_______________ is a recommended Model for Pattern Recognition in Unlabeled Data.

Recurrent Networks work best for Speech Recognition.

GPU stands for __________.

________________ works best for Image Data.

Neural Networks Algorithms are inspired from the structure and functioning of the Human Biological Neuron.

In a Neural Network, all the edges and nodes have the same Weight and Bias values.

What is the method to overcome the Decay of Information through time in RNN known as?

Process of improving the accuracy of a Neural Network is called _______________.

Data Collected from Survey results is an example of ___________________.

A Shallow Neural Network has only one hidden layer between Input and Output layers.

Support Vector Machines, Naive Bayes and Logistic Regression are used for solving

What does LSTM stand for?

All the Visible Layers in a Restricted Boltzmannn Machine are connected to each other.

All the neurons in a convolution layer have different Weights and Biases.

Recurrent Neural Networks are best suited for Text Processing.

Autoencoders cannot be used for Dimensionality Reduction.

What is the difference between the actual output and generated output known as?

Gradient at a given layer is the product of all gradients at the previous layers.

Prediction Accuracy of a Neural Network depends on _ and .

Restricted Boltzmann Machine expects the data to be labeled for Training.

Recurrent Network can input Sequence of Data Points and Produce a Sequence of Output.

_____________________ is a Neural Nets way of classifying inputs.

A Deep Belief Network is a stack of Restricted Boltzmann Machines.

Name the component of a Neural Network where the true value of the input is not observed.

Why is the Pooling Layer used in a Convolution Neural Network?

What is the best Neural Network Model for Temporal Data?

RELU stands for ______________________________.

What are the two layers of a Restricted Boltzmann Machine called?

How do RNTS interpret words?

Autoencoders are trained using _____________________.

The rate at which cost changes with respect to weight or bias is called __________________.

A _________________ matches or surpasses the output of an individual neuron to a visual stimuli.

Deep Learning Questions Answers

Explore topic-wise InterviewSolutions in .

The measure of Difference between two probability distributions is know as ________________________.

_______________ is a recommended Model for Pattern Recognition in Unlabeled Data.

Recurrent Networks work best for Speech Recognition.

GPU stands for __________.

________________ works best for Image Data.

Neural Networks Algorithms are inspired from the structure and functioning of the Human Biological Neuron.

In a Neural Network, all the edges and nodes have the same Weight and Bias values.

What is the method to overcome the Decay of Information through time in RNN known as?

Process of improving the accuracy of a Neural Network is called _______________.

Data Collected from Survey results is an example of ___________________.

A Shallow Neural Network has only one hidden layer between Input and Output layers.

Support Vector Machines, Naive Bayes and Logistic Regression are used for solving

What does LSTM stand for?

All the Visible Layers in a Restricted Boltzmannn Machine are connected to each other.

All the neurons in a convolution layer have different Weights and Biases.

Recurrent Neural Networks are best suited for Text Processing.

Autoencoders cannot be used for Dimensionality Reduction.

What is the difference between the actual output and generated output known as?

Gradient at a given layer is the product of all gradients at the previous layers.

Prediction Accuracy of a Neural Network depends on _______________ and ______________.

Restricted Boltzmann Machine expects the data to be labeled for Training.

Recurrent Network can input Sequence of Data Points and Produce a Sequence of Output.

_____________________ is a Neural Nets way of classifying inputs.

A Deep Belief Network is a stack of Restricted Boltzmann Machines.

Name the component of a Neural Network where the true value of the input is not observed.

Why is the Pooling Layer used in a Convolution Neural Network?

What is the best Neural Network Model for Temporal Data?

RELU stands for ______________________________.

What are the two layers of a Restricted Boltzmann Machine called?

How do RNTS interpret words?

Autoencoders are trained using _____________________.

The rate at which cost changes with respect to weight or bias is called __________________.

A _________________ matches or surpasses the output of an individual neuron to a visual stimuli.

Deep Learning Questions Answers

Prediction Accuracy of a Neural Network depends on _ and .