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Free HCIA-AI V3.5 Exam Practice Questions

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Exam style questions across every H13-311_V3.5 domain

Last Update 1 day ago
Total Questions : 60

Start with our free H13-311_V3.5 practice questions, carefully crafted to mirror the domains, phrasing, and difficulty of the real HCIA-AI exam. Each H13-311_V3.5 exam question comes with a detailed rationale that explains not just which answer is correct but why the others fall short. That's how concepts stick. Use the free set to benchmark yourself: identify your Huawei weak domains, see where you're losing marks, and build a focused study plan in minutes.

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Question # 1

When feature engineering is complete, which of the following is not a step in the decision tree building process?

Options:

A.  

Decision tree generation

B.  

Pruning

C.  

Feature selection

D.  

Data cleansing

Discussion 0
Question # 2

As we understand more about machine learning, we will find that its scope is constantly changing over time.

Options:

A.  

TRUE

B.  

FALSE

Discussion 0
Question # 3

Huawei Cloud EI provides knowledge graph, OCR, machine translation, and the Celia (virtual assistant) development platform.

Options:

A.  

TRUE

B.  

FALSE

Discussion 0
Question # 4

The core of the MindSpore training data processing engine is to efficiently and flexibly convert training samples (datasets) to MindRecord and provide them to the training network for training.

Options:

A.  

TRUE

B.  

FALSE

Discussion 0
Question # 5

Which of the following is NOT a commonly used AI computing framework?

Options:

A.  

PyTorch

B.  

MindSpore

C.  

TensorFlow

D.  

OpenCV

Discussion 0
Question # 6

Which of the following does not belong to the process for constructing a knowledge graph?

Options:

A.  

Determining the target domain of the knowledge graph

B.  

Data acquisition

C.  

Creating new concepts

D.  

Knowledge fusion

Discussion 0
Question # 7

Which of the following statements is false about gradient descent algorithms?

Options:

A.  

Each time the global gradient updates its weight, all training samples need to be calculated.

B.  

When GPUs are used for parallel computing, the mini-batch gradient descent (MBGD) takes less time than the stochastic gradient descent (SGD) to complete an epoch.

C.  

The global gradient descent is relatively stable, which helps the model converge to the global extremum.

D.  

When there are too many samples and GPUs are not used for parallel computing, the convergence process of the global gradient algorithm is time-consuming.

Discussion 0
Question # 8

"AI application fields include only computer vision and speech processing." Which of the following is true about this statement?

Options:

A.  

This statement is false. The application fields of AI include computer vision, speech processing, natural language processing, and others.

B.  

This statement is false. AI application fields include only computer vision and natural language processing.

C.  

This statement is true. Voice data is processed with extremely high accuracy.

D.  

This statement is true. Computer vision is the most important AI application.

Discussion 0
Question # 9

Sigmoid, tanh, and softsign activation functions cannot avoid vanishing gradient problems when the network is deep.

Options:

A.  

TRUE

B.  

FALSE

Discussion 0
Question # 10

The general process of building a project using machine learning involves the following steps: split data, _________________ the model, deploy the model the model, and fine-tune the model.

Options:

Discussion 0

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