 

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)Denoising 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  



