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Study notes > HCIA AI practice exam 1 > Flashcards

HCIA AI practice exam 1 Flashcards

1
Q

1.) What are the element of AI?

Select one or more:

a. Scenarios
b. Algorithms
c. Data
d. Computing power

A

Computing Power
Algorithms
Scenarios
Data

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2
Q

2.) Speech processing is a general term for various processing technologies used to research the voicing process, statistical features of speech signals, speech recognition

True
False

A

True

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3
Q
  1. Which of the following belong to Howard Gardner(human intelligence)?

a.Language
b. Space
c.Logic
d. Music

A

Space, Language, Music, Logic

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4
Q
  1. What are the application scenarios of computing vision?

a. Smart album
b. Action analysis
c. Voice navigation
d. Image search

A

Action analysis, image search, smart album

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5
Q
  1. The three phases of AI include computingg intelligence, (), and cognitive intelligence.

Select one:

Behavior Intelligence
Strong AI
Perceptual Intelligence
Narrow AI

A

Perceptual Intelligence

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6
Q
  1. Neural networks are not a type of machine learning

True
False

A

False

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7
Q
  1. Which of the following is not integrated learning policy in machine learning algorithms?

Select one:
Stacking
Bagging
Marking
Boosting

A

Marking

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8
Q
  1. In machine learning, which of the following is not a part of the process from obtaining data to officially putting the data into a model?

Select one:
Data standardization
Data cleansing
Data visualization
Data dimension deduction

A

Data visualization

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9
Q
  1. The test error keep decreasing as model complexity increases

True
False

A

True

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10
Q
  1. If an enterprise has a large amount of sales data without labels, which of the following models are suitable for the enterprise to identify VIP customers?

Select one or more:
SVM
Logistic Regression
K-Means
Hierarchical clustering

A

Hierarchical clustering, k-means

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11
Q
  1. Which of the following are common clustering algorithms

Select one or more:

Spectral Clustering
K-means
Hierarchical clustering
Density-based clustering

A

K-means, Spectral clustering, Density-based clustering, Hierarchical clustering

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12
Q
  1. Which of the following problems can be resolved by using machine learning algorithms?

Select one or more:
Reinforcement problem
Clustering problem
Classification problem
Regression problem

A

Clustering problem, Classification problem, regression problem

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13
Q
  1. Which of the following is an evaluation indicator of regression algorithms?

Select one:
Mean squared error
Accuracy
Confusion matrix
Recall

A

Mean squared error

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14
Q
  1. The naive Bayes algorithms does not require sample feature to e independent and identically distributed.

Select one:
True
False

A

False

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15
Q
  1. What is the correct overall process of machine learning?
A

Data collection
Data cleansing
Feature extraction and selection
Model Training
Model evaluation and test
Model deployment and integration

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16
Q

The F1 value for evaluation classification models is the harmonic mean of indicators including ().

Select one or more:

Precision
Accuracy
Recall
Validity

A

Recall, Precision

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17
Q

Which of the following points constitute support vectors in the SVM without considering regular expressions?

Select one:

Points of a certain class
Points on the separating hyperplane
Points nearest to the separating hyperplane
Points farthest from the separating hyperplane

A

Points nearest to the separating hyperplane

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18
Q
  1. About the following code: SVR(kernel-‘rbf’, C=1e3, gamma= 0.01), it means that we use linear kernel functions.

Select one:
True
False

A

False

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19
Q
  1. A loss function reflects an error between a target output and an actual output of a neural network. Which of the following is a common loss function in deep learning?

Select one:
Logarithmic loss function
Mean square loss function
Hinge loss function
Exponential loss function

A

Mean square loss function

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20
Q
  1. If each later of a neural network uses the Sigmoid activation function and the number of the layer is large, which of the following problems will occur?

select one:
Gradient explosion problem
Overfitting problem
Vanishing gradient problem
Underfitting problem

A

Vanishing gradient problem

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21
Q
  1. Perceptron is the simplest neural network among all deep learning neural networks. Which of the following statements about the perceptron’s structure is correct?

Select one:

The perceptron uses the ReLU activation function
The perceptron has no hidden layer
The perceptron uses the Sigmoid activation function
The perceptron has two hidden layers

A

The perceptron has no hidden layer

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22
Q
  1. Which of the following methods can be used to resolve data imbalance problems in deep learning tasks?

Select one or more:

Batch deletion
Synthetic sampling
Random oversampling
Random undersampling

A

Synthetic sampling, Random oversampling, Random undersampling

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23
Q
  1. Convolutional neural networks are widely used in the field of image processing. Which of the following is not a part of a convolutional neural network?

Select one:
Pooling layer
Fully-connected layer
convolutional layer
Bidirectional hidden layer

A

Bidirectional hidden layer

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24
Q
  1. Currently, generative adversarial network are widely used. Which of the following scenarios can use such networks?

Information retrieval
Image generation
Semantic segmentation
Data augmentation

A

All of the above

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25
Q
  1. An activation function is used to convert linear mapping into nonlinear mapping.

True
False

A

True

26
Q
  1. Overfitting means that a model performs well on a training set but poorly on a test set. Which of the following methods can be used to avoid overfitting?

Select one or more:

Early stopping of training
Dropout method
L1 and L2 regularization
Dataset expansion

A

all of the above

27
Q
  1. How should samples in real datasets be used in Generative Adversarial Networks (GAN)?

Select one:

Used as the input value of the generative model
Used as the output value of the generative model
Used as the output value of the discriminative model
Used as the input value of the discriminative model

A

Used as the input value of the discriminative model

28
Q
  1. Regularization is an important and effective technology for reducing generalization errors in traditional machine learning. Which of the following are regularization technologies?

Select one or more:

L1 regularization
L2 regularization
Momentum optimizer
Dropout

A

Dropout, L1 regularization, L2 regularization

29
Q
  1. Which of the following optimizers can automatically adjust the learning rate?

Select one:
SGD algorithm
Momentum optimizer
Mini-batch gradient descent algorithm
AdaGrad optimizer

A

AdaGrad optimizer

30
Q
  1. As an important part of a neural network, activation functions are classified into various types. Which of the following functions are activation functions

Select one or more:
ReLU function
Sigmoid function
SoftPlus function
Tanh function

A

all of the above

31
Q
  1. Which of the following statements about neural networks is incorrect?

Select one:

a. As hidden layers of a neural network increase, the model classification capability gradually weakens.
b. The limitation of a single-layer perception is that it cannot resolve XOR problems.
c. A feedforward neural network can be represented using a directed acyclic graph
d. The neurons at the same layer of the feedforward neural network are not interconnected

A

a.

32
Q
  1. Which of the following statements about a convolutional neural networks is incorrect?

Select one:
a. During image processing, image convolutional is performed through window scanning.
b. a convolutional neural network can include convolutional layers, pooling layers, and fully-connected layers
c. a convolutional kernel cannot be used to extract global features of images.
d. Common pooling layers include the max-pooling layer and average-pooling layer.

A

c. A convolutional kernel cannot be used to extract global features of images

33
Q
  1. All convolutional kernels of the same covolutional layer on a convolutional neural network share a weight

True
False

A

False

34
Q
  1. Which of the following operators is not supported by TensorFLow 2.0?

Select one:
//
pow
(^) (wa ni parenthesis dma kita gd)
@

A

(^)

35
Q
  1. tf.keras.datasets can be used to view Keras built-in datasets.

True
False

A

True

36
Q
  1. Which of the following steps belong to TensorFLow development process?

Select one or more:

Data preparation
Network construction
Model restoration and invoking
Model training and verification

A

all of the above

37
Q
  1. Which of the following are built-in loss function of tf.keras.losses?

Select one or more

BInary cross entropy loss
Likelihood
Mean square error
Mean absolute percentage error loss

A

Binary cross entropy loss, Mean square error, Mean absolute percentage error loss

38
Q
  1. Which of the following methods can be used for tensor combination in TensorFlow 2.0?

Select one:
Join
Split
concat
unstack

A

concat

39
Q
  1. Which of the following methods is used for network compilation when the Keras interface of TensorFlow 2.0 is used to build a neural networks?

Select one:
join
fit
write
compile

A

compile

40
Q
  1. Which of the following does not support dimension conversion in TensorFlow 2.0?

Select one:

reshape
squeeze
gather
transpose

A

gather

41
Q
  1. The graph and session mechanism is deleted from TensorFlow 2.0

True
False

A

True

42
Q
  1. which of the following are AI training and inference frameworks?

Select one or more:
MindSpore
PyTorch
TensorFlow
Pandas

A

PyTorch, TensorFlow, MindSpore

43
Q
  1. The typical application development process of the application development service does not include data loading.

True
False

A

False

44
Q
  1. Which of the following is not a common operation of MinsSpore?

Select one:
signal
nn
array
math

A

signal

45
Q
  1. MindSpore can use only Huawei-developed Ascend processors for training and inference.

Select one:
True
False

A

False

46
Q
  1. Which of the following technology innovations is not used by MindSpore to bridge the huge gap between industry research and all-scenario AI applications and facilitate inclusive AI?

Select one:
New programming paradigm
New programming language
New way of cooperation
New execution paradigm

A

New programming language

47
Q
  1. Bonus
A

bonus

48
Q
  1. The CPU improves AI performance by adding instruction and cores.

True
False

A

True

49
Q
  1. Which of the following computing resources are included in the Da Vinci architecture?

Select one or more:
Scalar unit
Cube unit
Vector unit
Tensor unit

A

Cube, Vector, Scalar

50
Q
  1. The GPU is good at processing easy-to-parallel programs with intensive computing

Select one:
True
False

A

True

51
Q
  1. There are multiple models of Atlas 800 AI servers. Which of the following are based on the Kunpeng processor platform?

Select one or more:
Atlas 800 (model 3000)
Atlas 800 (model 3010)
Atlas 800 (model 9000)

A

Atlas 800(model 9000), Atlas 800 (model 3000)

52
Q
  1. What are the advantages of the HIAI mobile computing platform?

Select one or more:
Source code enabling quick start
Various tool chains
Comprehensive documents
Different types of APIs

A

all of the above

53
Q
  1. Which of the following functions is provided by Huawei hiai foundation module?

Select one:
Enable services to automatically target and acquire users
Integrate apps
quickly convert and port existing models
Push services based on user requirements

A

Quickly convert and port existing models

54
Q
  1. HiAI Engine opens app capabilities and integrates multiple AI capabilities into apps, making apps smarter and more powerful. What can apps benefit from Huawei HiAI?

Select one or more:
Lower cost
Security
Ready-to-use
Stability

A

all of the above

55
Q
  1. Which of the following scenarios can Enterprise Intelligence( EI) be applied to?

Select one or more:
Smart City
Smart government
Smart manufacturing
Smart finance

A

all of the above

56
Q
  1. Which of the following services belong to the Huawei EI service family?

Select one or more:
Natural language processing
Basic EI services
EI big data services
Conversational bot service (CBS)

A

all of the above

57
Q
  1. Which of the following are correct statements about the product advantages of the ModelArts AI development platform?

Select one or more:
One-stop platform
Flexibility
Easy of use
High performance

A

All of the above

58
Q
  1. Which of the following is not the application of the image recognition service?

Select one:
Scenario analysis
Smart Album
Speech synthesis
Object detection

A

Speech synthesis

59
Q
  1. Which of the following services can be used together with ModelArts to easily deploy models on devices?

Select one
Hilens
ECS
OBS
OCR

A

HiLens

60
Q
  1. Which one doesnt belong to huawei EI Essential Platform?

Select one:
ModelArts
Huawei HiLens
Huawei HiAI
Graph Engine Service (GES)

A

Huawei HiAI

Study notes (3 decks)

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