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Keras Multiple-Choice Questions (MCQs)

Keras is an open-source software library that provides a Python interface for artificial neural networks. Keras acts as an interface for the TensorFlow library.

Keras MCQs: This section contains multiple-choice questions and answers on the various topics of Keras. Practice these MCQs to test and enhance your skills on Keras.

List of Keras MCQs

1. Keras is a ____.

  1. Data science library
  2. Neural network library
  3. Data testing library

Answer: B) Neural network library

Explanation:

Keras is a neural network library.

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2. Keras is written in which language?

  1. Spark
  2. Java
  3. C
  4. C++
  5. Python

Answer: E) Python

Explanation:

Keras is written in python language.

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3. Who developed Keras?

  1. Pete Shinners
  2. Wes McKinney
  3. François Chollet

Answer: C) François Chollet

Explanation:

Keras was developed by François Chollet.

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4. Does Keras support convolutional or recurrent neural networks?

  1. Yes, it supports both
  2. Yes, it only supports convolutional network
  3. Yes, it only supports recurrent neural network
  4. None

Answer: A) Yes, it supports both

Explanation:

Yes, Keras supports convolutional or recurrent neural networks both and it also supports their combination.

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5. Does Keras handle low-level computations?

  1. Yes
  2. No

Answer: B) No

Explanation:

No, Keras cannot handle low-level computations.

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6. How many backend engines does Keras consist of?

  1. 2
  2. 3
  3. 4
  4. 9

Answer: B) 3

Explanation:

Keras consist of three backend engines: Tensor flow, Theano, CNTK.

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7. TensorFlow is a product of which company?

  1. Oracle
  2. Microsoft
  3. Google
  4. IBM

Answer: C) Google

Explanation:

TenserFlow is the product of Google.

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8. Which of the following activities are performed by TensorFlow?

  1. Data automation
  2. Model tracking
  3. Model retraining
  4. Performance monitoring
  5. All of the above

Answer: E) All of the above

Explanation:

TensorFlow helps us to perform the following activities:

  • Data automation
  • Model tracking
  • Model retraining
  • Performance monitoring

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9. TensorFlow can be only used with python?

  1. Yes
  2. No
  3. Except python every language

Answer: B) NO

Explanation:

TensorFlow can be used with wide variety of languages: Python, JavaScript, C++, and Java

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10. Which kind of library Theano is?

  1. Machine learning
  2. Artificial intelligence
  3. Mathematical operation
  4. None of the above
  5. All of the above

Answer: C) Mathematical operation

Explanation:

Theano library performs mathematical operations on multi-dimensional arrays.

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11. Does Keras support multiple platforms?

  1. Yes
  2. No

Answer: A) YES

Explanation:

Yes, Keras support multiple platforms.

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12. To revert back to the current name of the backend, which of the following backend functions would you use in Keras?

  1. Backend()
  2. keras.backend.backend()
  3. Backend.keras()

Answer: B) keras.backend.backend()

Explanation:

keras.backend.backend() is used to revert to the current name of the backend.

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13. tf.keras.backend.set_floatx(value) will return ____?

  1. Returns the default float type, as a string.
  2. Returns the default float type, as a float number.
  3. Returns the default float type, as an integer.
  4. Returns the default float and integer type, as a string.

Answer: A) Returns the default float type, as a string.

Explanation:

tf.keras.backend.set_floatx(value), will return the default float type, as a string.

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14. Which backend function in Keras returns the default image data format convention?

  1. Format_image()
  2. Image_format_data()
  3. image_data_format()
  4. image_format()

Answer: C) image_data_format()

Explanation:

image_data_format function in Keras returns the default image data format convention.

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15. What is the return value of the epsilon function?

  1. It returns the absolute factor
  2. It returns the fuzz factor
  3. It returns the factorization of all the numbers used in an expression
  4. It returns the floor division of an expression

Answer: B) It returns the fuzz factor

Explanation:

The epsilon function returns the fuzz factor.

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16. How many arguments does the placeholder function take, in Keras?

  1. 2
  2. 4
  3. 5
  4. 6

Answer: C) 5

Explanation:

Placeholder function takes 5 arguments:

  • shape
  • Ndim
  • dtype
  • Sparse
  • name

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17. How many types of models does Keras provide?

  1. 2
  2. 3
  3. 4
  4. 5

Answer: A) 2

Explanation:

Keras provides two types of models: A sequential Model and an advanced Model.

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18. The layers within the sequential models are known as ____?

  1. Sequential API
  2. Sequential Layer
  3. Sequential processes

Answer: A) Sequential API

Explanation:

The layers within the sequential models are known as sequential API.

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19. Which of the following Keras models is known to be the simplest model and it constitutes a linear set of layers?

  1. Sequential Model
  2. Advanced Model

Answer: A) Sequential Model

Explanation:

Sequential Keras model is known to be the simplest model and it constitutes a linear set of layers.

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20. Which of the following methods is used to add layers in a sequential model?

  1. Layers_add()
  2. Add_layers()
  3. Add()
  4. Layers()

Answer: C) Add()

Explanation:

Add() method is used to add layers in a sequential model.

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21. How many parameters does the compilation process take in Keras?

  1. 3
  2. 5
  3. 9
  4. 6

Answer: A) 3

Explanation:

Three parameters that the compilation process takes in Keras: An optimizer, A loss function, and A list of metrics.

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22. What is LSTM?

  1. Longitude short-term memory
  2. Long short-term memory
  3. Lengthy short-term memory

Answer: B) Long short-term memory

Explanation:

LSTM stands for Long short-term memory.

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23. Why do we use LSTM?

  1. To learn sequential data
  2. To process sequential data
  3. To classify sequential data
  4. All of the above.

Answer: D) All of the above.

Explanation:

LSTM is used to learn, process, to classify sequential data.

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24. Is Keras functional API and Keras sequential API the same?

  1. Yes
  2. No

Answer: B) NO

Explanation:

Keras functional API is more flexible than Keras sequential API.

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25. Models with shared layers, multi-outputs, and directed acyclic graphs can be defined using the ____?

  1. Keras functional API
  2. Keras sequential API

Answer: A) Keras functional API

Explanation:

Models with shared layers, multi-outputs, and directed acyclic graphs can be defined using the Keras functional API.

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26. Which of the following API arranges the Keras layers in sequential order?

  1. Keras functional API
  2. Keras sequential API

Answer: B) Keras sequential API

Explanation:

Keras Sequential API arranges the Keras layers in sequential order.

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27. To implement a densely-connected network, which of the following model gives better results?

  1. Sequential model
  2. Advanced model

Answer: A) Sequential model

Explanation:

Sequential model results better to implement a densely-connected network.

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28. The functional API can handle models with ____topology?

  1. Linear
  2. Non-linear
  3. Advanced model

Answer: A) Linear

Explanation:

The functional API can handle models with non-linear topology

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29. Does Keras allow you to create your own layer?

  1. Yes
  2. No

Answer: A) YES

Explanation:

Yes, we can create layers in Keras, and also it provides us with predefined layers.

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30. Which layer in Keras is a widely used layer for creating a deeply connected layer in the neural network?

  1. Flatten layer
  2. Dropout layer
  3. Dense layer
  4. Permute layer

Answer: C) Dense layer

Explanation:

Dense layer in Keras is widely used Keras layer for creating a deeply connected layer in the neural network.

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31. Which of the following layers in Keras is used for flattening the input?

  1. Flatten layer
  2. Dropout layer
  3. Pooling layer
  4. Permute layer

Answer: A) Flatten layer

Explanation:

Flatten layer in Keras is used for flattening the input.

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32. which Keras layer would you use if you want to reduce overfitting in neural network models?

  1. Pooling layer
  2. Dropout layer
  3. Permute layer
  4. Lambda layer

Answer: B) Dropout layer

Explanation:

We will use the Dropout layer if we want to reduce overfitting in neural network models.

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33. Which of the following layers is capable of altering the shape of the input?

  1. Pooling layer
  2. Dropout layer
  3. Permute layer
  4. Reshape layer

Answer: D) Reshape layer

Explanation:

Reshape layer is capable of altering the shape of the input.

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34. Which Keras layer would you use if you want to repeat the input a fixed number of times?

  1. Pooling layer
  2. Repeatvector layer
  3. Permute layer
  4. Lambda layer

Answer: B) Repeatvector layer

Explanation:

RepeatVector layer will repeat the input a fixed number of times.

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35. In Keras, "dense" refers to a ____ layer.

  1. Single
  2. Multiple
  3. Linear
  4. Non-linear

Answer: A) Single

Explanation:

In Keras, "dense" refers to a single layer.

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36. In Keras, "sequential" refers to a ____?

  1. Single layer
  2. Multiple layers
  3. Entire model

Answer: C) Entire model

Explanation:

In Keras, "sequential" refers to an entire model.

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37. What does sequential.pop() method do?

  1. It helps in the removal of the first layer from the model.
  2. It helps in the removal of the last layer from the model.
  3. It helps in the removal of any layer from the model.

Answer: B) It helps in the removal of the last layer from the model.

Explanation:

Sequential.pop() functions help in the removal of the last layer from the model.

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38. When sequential.pop() method raises a TypeError?

  1. When there is no layer within the model
  2. When there is the single layer within the model
  3. When there are more than 10 layers within the model

Answer: B) When there is the single layer within the model

Explanation:

sequential.pop() method raises a TypeError When there is a single layer within the model.

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39. Which of the following layers is used to wrap up an arbitrary expression?

  1. Pooling layer
  2. Repeatvector layer
  3. Permute layer
  4. Lambda layer

Answer: D) Lambda layer

Explanation:

The lambda layer is used to wrap up an arbitrary expression.

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40. Which layer acts as a base class for the recurrent layers?

  1. Pooling layer
  2. Repeatvector layer
  3. Permute layer
  4. Lambda layer
  5. RNN layer

Answer: E) RNN layer

Explanation:

RNN layers act as a base class for the recurrent layers.

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41. Which layer in Keras supports masking?

  1. Pooling layer
  2. Repeatvector layer
  3. Permute layer
  4. Embedding layer
  5. RNN layer

Answer: D) Embedding layer

Explanation:

Embedding layers in Keras support masking.

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42. Which of the following is a fully connected layer whose output is sent back to the input?

  1. Pooling layer
  2. SimpleRNN layer
  3. Embedding layer
  4. RNN layer

Answer: B) SimpleRNN layer

Explanation:

SimpleRNN layer is a fully connected layer whose output is sent back to the input.

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43. What is GRU in Keras?

  1. Granted Recurrent unit
  2. Gated Recurrent unit
  3. Great recurrent unit

Answer: B) Gated Recurrent unit

Explanation:

GRU stands for the grated recurrent unit.

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44. Who introduced LSTM?

  1. Pete Shinners
  2. Wes McKinney
  3. François Chollet
  4. Hochreiter

Answer: D) Hochreiter

Explanation:

LSTM was introduced by Hochreiter.

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45. Does Keras run on a GPU?

  1. Yes
  2. No

Answer: A) YES

Explanation:

Keras run smoothly on GPU and CPU.

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46. Which of the following companies uses Keras?

  1. Netflix
  2. Uber
  3. Yelp
  4. All of the above

Answer: D) All of the above

Explanation:

Companies like Netflix, Uber, and Yelp use Keras.

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47. Which of the following functions offers you the list of all the input tensors in a model?

  1. Models.inputs()
  2. Input. Models()
  3. Inputs()

Answer: A) Models.inputs()

Explanation:

Model.inputs() function offers you the list of all the input tensors in a model.

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48. To train your model in Keras, which of the following methods would you use?

  1. Predict()
  2. Model()
  3. Fit()

Answer: C) Fit()

Explanation:

The fit method is used to train the model in Keras.

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49. To predict your model, which of the following methods would you use?

  1. Predict()
  2. Model()
  3. Fit()

Answer: A) Predict()

Explanation:

Predict method is used to predict the model.

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50. Which functions in Keras help you to find faults or deviations in the learning process?

  1. Keras optimizer function
  2. Keras metrics
  3. Keras loss function

Answer: C) Keras loss function

Explanation:

Keras loss function in Keras helps you to find faults or deviations in the learning process.

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51. Which of the following permits you to evaluate the performance of your model?

  1. Keras optimizer function
  2. Keras metrics
  3. Keras loss function

Answer: B) Keras metrics

Explanation:

Keras metrics permit you to evaluate the performance of your model.

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52. In which of the following layers, input is transformed into a standardized form?

  1. Normalization Layer
  2. Pooling Layer
  3. Noise Layer
  4. Recurrent Layer

Answer: A) Normalization Layer

Explanation:

In normalization, layer input is transformed into a standardized form.

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53. In how many ways can you include your customized layer in Keras?

  1. 2
  2. 3
  3. 4
  4. 5

Answer: A) 2

Explanation:

There are two ways in which you can customize the layer:Custom Class Layer, and Lambda Layer.

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54. Which of the following backend functions in Keras offers you to enter the Keras graph?

  1. Eager()
  2. Backend()
  3. Shape()
  4. Symbolic()

Answer: D) Symbolic()

Explanation:

Symbolic() backend function in Keras offers you to enter the Keras graph.

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55. Which of the following principles does Keras follow to perform deep learning efficiently?

  1. Modularity
  2. User-friendliness
  3. Extensibility
  4. All of the above

Answer: D) All of the above

Explanation:

Modularity, User-friendliness, and Extensibility principle does Keras follow to perform deep learning efficiently.

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56. ____ are the basic units of Convolutional Neural Networks?

  1. Neurons
  2. Pooling
  3. ReLU

Answer: A) Neurons

Explanation:

Neurons are the basic units of Convolutional Neural Networks.

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57. How many layers does CNN consist of?

  1. 2
  2. 3
  3. 4
  4. 5

Answer: B) 3

Explanation:

CNN consists of 3 layers: a pooling layer, and a fully connected layer, a convolutional layer.

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58. What do you mean by OpenCV?

  1. Open source common vision
  2. Open-source common visualization
  3. Open-source computer vision

Answer: C) Open-source computer vision

Explanation:

OpenCV is known as Open-source computer vision.

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59. OpenCV is useful for ____?

  1. Machine learning
  2. Computer vision
  3. Both
  4. Only A
  5. Only B

Answer: C) Both

Explanation:

OpenCV is useful for Machine learning and Computer vision.

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60. Is OpenCV a platform-independent library?

  1. Yes
  2. No

Answer: A) YES

Explanation:

OpenCV is platform-independent. It supports a variety of platforms.

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61. Which is more efficient, Keras or OpenCV?

  1. OpenCV
  2. Keras

Answer: B) Keras

Explanation:

Keras is more efficient than OpenCV.

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62. Which is slower, Keras or TensorFlow?

  1. Keras
  2. TensorFlow

Answer: A) Keras

Explanation:

Keras is slower than TensorFlow.

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63. Which of the following has simpler architecture?

  1. Keras
  2. TensorFlow

Answer: A) Keras

Explanation:

Keras has simpler architecture than TensorFlow.

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64. Is Keras capable of handling complex datasets?

  1. Yes
  2. No

Answer: B) NO

Explanation:

Keras is good with smaller datasets but not with complex datasets.

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65. Is TensorFlow capable of handling complex datasets?

  1. Yes
  2. No

Answer: A) YES

Explanation:

Yes, TensorFlow is good with smaller datasets as well as with complex datasets.

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