Deep Learning - Chorale Prelude MCQs Solution | TCS Fresco Play | Fresco Play | TCS

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Deep learning chorale prelude mcq solution

Deep learning chorale prelude course answer

Deep learning chorale prelude mcq answers

Deep learning chorale prelude

Deep learning chorale prelude fresco play course answer

Deep learning chorale prelude fresco play
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1. Data Collected from Survey results is an example of ______

structured data

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

TRUE

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

hidden layer

4. _______________ is a Neural Nets way of classifying inputs.

FP

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

weight and bias

6. Recurrent Networks work best for Speech Recognition.

TRUE

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

FALSE

8. Recurrent Neural Networks are best suited for Text Processing.

TRUE

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

TRUE

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

11. GPU stands for ________

graphic

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

cost

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

TRUE

14. _____________ is a recommended Model for Pattern Recognition in Unlabeled Data.

auto

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

training

16. Restricted Boltzmann Machine expect the data to be labeled for Training.

FALSE

17. What is the best Neural Network Model for Temporal Data?

recurrent

18. How do RNTS interpret words?

vector

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

TRUE

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

TRUE

hidden

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

FALSE

22. What is the best Neural Network Model for Temporal Data?

recuurent

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

hidden

24. RELU stands for ________

rectified linear

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

FALSE

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

dimension

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

FALSE

28. What does LSTM stand for?

long short term mem

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

FALSE

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

KL Diver

31. ___________ works best for Image Data.

convulsion

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

TRUE

33. Autoencoders cannot be used for Dimensionality Reduction.

FALSE

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

Gating

35. De-noising and Contractive are examples of _____________

autoencoder

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

cost

37. ________________ models are best suited for Recursive Data.

Recursive neutral tensor nets

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

Convolution

39. Support Vector Machines, Naïve Bayes and Logistic Regression are used for solving ___________________

problems Classification

40. How do RNTS interpret words?

Vector Representations

41. Autoencoders are trained using __________

feed

______________________________________

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

True

2.Recurrent Networks work best for Speech Recognition.

True

3.Data Collected from Survey results is an example of ___________________.

Structured data

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

True

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

Hidden layer

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

Training

7.GPU Stands for

Graphics Processing Unit

8.Support Vector Machines, Naïve Bayes and Logistic Regression are used for solving ___________________ problems.

classification

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

10._____________________ is a Neural Nets way of classifying inputs.

Learning(*)

Classification(*)

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

cost

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

weight and bias

13.________________ works best for Image Data.

Convolutional network

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

False

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

True

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

Autoencoders

17.What does LSTM stand for?

Long Short Term Memory

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

Convolution

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

False

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

True

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

KL Divergence

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

False

23.RELU stands for ______________________________.

Rectified Linear Unit

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

Hidden and visible layers

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

Dimension reduction

26.What is the best Neural Network Model for Temporal Data?

Recurrent Neural Networks

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

Gating

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

True

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

False

30.Autoencoders are trained using _____________________.

Reconstruction(*)

Feed Forward(*)

31.Autoencoders cannot be used for Dimensionality Reduction.

False

32.________________ works best for Image Data.

Convolution Networks

33.How do RNTS interpret words?

One hot encoding(*)

34.De-noising and Contractive are examples of __________________.

Auto encoder(*)

RNN

Multi layer perceptions

35.________________ models are best suited for Recursive Data.

Recursive neural network(*)

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