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無料Huawei H13-311_V3.5テスト練習問題試験問題集
Huawei H13-311_V3.5（HCIA-AI v3.5）認定試験は、90分で完了する必要がある60の複数選択質問で構成されています。この試験では、基本的なAIコンセプト、Pythonプログラミングの基礎、機械学習アルゴリズム、ディープラーニングモデル、一般的なAIアプリケーションシナリオなど、幅広いトピックをカバーしています。試験に合格した候補者は、Huaweiと業界によって認識される証明書を受け取ります。
この試験は、すでにAIの分野で働いている専門家や、このドメインに入ることを計画している専門家に最適です。また、人工知能のスキルと知識を高め、キャリアを次のレベルに引き上げることを望んでいる個人にも適しています。 HCIA-AI V3.5認定試験は、専門家が専門知識を紹介し、AIの分野へのコミットメントを実証する絶好の機会です。
質問 # 210
Which of the following activation functions are prone to vanishing gradient problems?
- A. Tanh
- B. Softplus
- C. ReLU
- D. Sigmoid
正解：A、D
質問 # 211
What is the most important difference between batch gradient descent, mini-batch gradient descent, and stochastic gradient descent?
- A. Gradient size
- B. Number of samples used
- C. Learning rate
- D. Gradient direction
正解：B
質問 # 212
Which of the following can improve the computational efficiency of the neural network model?
(Multjple choice)
- A. GPU
- B. TPU
- C. Large-scale distributed cluster
- D. FPGA
正解：A、B、C、D
質問 # 213
Which of the following is not a specific technology of artificial intelligence?
- A. Semantic understanding
- B. Knowledge map
- C. Riemann geometry
- D. Machine translation
正解：C
質問 # 214
There are many types of neural networks in deep learning. The following neural network information is one-way propagation:
- A. Convolutional Neural Network
- B. GRU
- C. LSTM
- D. Recurrent neural network
正解：A
質問 # 215
The loss function reflects the error between the target output and actual output of the neural network.
The commonly used loss function in deep learning is:
- A. Mean square loss function
- B. Exponential loss function
- C. Log loss function
- D. Hinge Loss function
正解：A
質問 # 216
TensorFlow2.0 The mechanism of graphs and conversations has been cancelled in.
- A. TRUE
- B. FALSE
正解：B
質問 # 217
Which of the following is HUAWEI HiAI Foundation Function of the module?
- A. App integrated
- B. According to user needs, push services at the right time and at the right time
- C. Let the service actively find users
- D. Quickly convert and migrate existing models
正解：D
質問 # 218
Which of the following about the gradient descent is incorrect?
- A. Random gradient descent is one of the commonly used optimization algorithms in deep learning algorithms.
- B. Gradient descent includes random gradient descent and batch gradient descent.
- C. Random gradient descent is a commonly used one in gradient descent.
- D. The gradient descent algorithm 1s fast and reliable [Right Answers}
正解：D
質問 # 219
The meaning of artificial intelligence was first proposed by a scientist in 1950, and at the same time a test model of machine intelligence was proposed Who is this scientist?
- A. Von Neumann
- B. Zade
- C. Minsky
- D. Turing
正解：D
質問 # 220
What quotation marks can the Python language use? (Multiple Choice)
- A. Single quotes
- B. Three quotes
- C. Double quotes
- D. Four quotes
正解：A、B、C
質問 # 221
Python is a fully object-oriented language.
Which of the following options belong to the Python object? (Multiple Choice)
- A. Module
- B. Function
- C. Number
- D. Character string
正解：A、B、C、D
質問 # 222
The loss function of logistic regression is the cross-entropy loss function.
- A. FALSE
- B. TRUE
正解：B
質問 # 223
The trace operation returns the sum of the diagonal elements of the matrix. Therefore, the trace of matrix A and its transposed matrix are equal
- A. True
- B. False
正解：A
質問 # 224
Where should the labeled data be placed in the confrontation generation network?
- A. As the input value of the discriminant model
- B. As the output value of the discriminant model
- C. As the output value of the generated model
- D. As input value for generative model
正解：A
質問 # 225
" print" in Python 3 must be used with "()"
- A. True
- B. False
正解：A
質問 # 226
When feature engineering is complete, which of the following is not a step in the decision tree building process?
- A. Decision tree generation
- B. Data cleansing
- C. Pruning
- D. Feature selection
正解：B
解説：
When building a decision tree, the steps generally involve:
Decision tree generation: This is the process where the model iteratively splits the data based on feature values to form branches.
Pruning: This step occurs post-generation, where unnecessary branches are removed to reduce overfitting and enhance generalization.
Feature selection: This is part of decision tree construction, where relevant features are selected at each node to determine how the tree branches.
Data cleansing, on the other hand, is a preprocessing step carried out before any model training begins. It involves handling missing or erroneous data to improve the quality of the dataset but is not part of the decision tree building process itself.
HCIA AI
Reference:
Machine Learning Overview: Includes a discussion on decision tree algorithms and the process of building decision trees.
AI Development Framework: Highlights the steps for building machine learning models, separating data preprocessing (e.g., data cleansing) from model building steps.
質問 # 227
Which of the following description of the validation set is wrong?
- A. The subset used to pick hyperparameters is called a validation set
- B. Typically 80% of the training data 1s used for training and 20% 1s used for verification.
- C. The test set can coincide with the training set
- D. The verification set can coincide with the test set.
正解：D
質問 # 228
On-Device Execution, that is, the entire image is offloaded and executed, and the computing power of the Yiteng chip can be fully utilized, which can greatly reduce the interaction overhead, thereby increasing the accelerator occupancy rate.
On-Device The following description is wrong?
- A. MindSpore Through the chip-oriented depth map optimization technology, the synchronization wait is less, and the "data computing communication" is maximized. The parallelism of "trust", compared with training performance Host Side view scheduling method is flat
- B. Challenges of model execution under super chip computing power: Memory wall problems, high interaction overhead, and difficulty in data supply. Partly in Host Executed, partly in Device Execution, interaction overhead is even much greater than execution overhead, resulting in low accelerator occupancy
- C. The challenge of distributed gradient aggregation under super chip computing power:ReslNet50 Single iteration 20ms Time will be generated The synchronization overhead of heart control and the communication overhead of frequent synchronization. Traditional methods require 3 Synchronization completed A11 Reduce, Data-driven method autonomy A11 Reduce, No control overhead
- D. MindSpore Realize decentralized autonomy through adaptive graph optimization driven by gradient data A11 Reduce, Gradient aggregation is in step, and calculation and communication are fully streamlined
正解：A
質問 # 229
Which of the following statements about universal form recognition services are correct?
- A. The incoming image data needs to go through base64 coding
- B. rows Represents the line information occupied by the text block, the number is from 0 Start, list form
- C. colums Represents the column information occupied by the text block, the number is from 0 Start, list form
- D. words Representative text block recognition result
正解：A、B、C、D
質問 # 230
In a neural network, knowing the weight and deviations of each neuron is the most important step. If you know the exact weights and deviations of neurons in some way, you can approximate any function What is the best way to achieve this?
- A. Assign an initial value to iteratively update weight by checking the difference between the best value and the initial
- B. Random assignment, pray that they are correct
- C. The above is not correct
- D. Search for a combmat1on of weight and deviation until the best value 1s obtained
正解：A
質問 # 231
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