H13-311_V3.5 Exam questions, H13-311_V3.5 Braindumps, H13-311_V3.5 Real Exams

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Huawei H13-311_V3.5 exam is a certification for those who are interested in learning about artificial intelligence and its applications. H13-311_V3.5 exam is designed for individuals who want to become certified in the HCIA-AI field and want to demonstrate their expertise in machine learning.

Huawei H13-311_V3.5 (HCIA-AI V3.5) Certification Exam is an excellent opportunity for individuals to validate their skills and knowledge in the field of artificial intelligence. H13-311_V3.5 exam covers a broad range of topics and is suitable for both beginners and professionals. Obtaining this certification can help individuals advance their careers in AI and gain a competitive edge in the job market.

Huawei H13-311_V3.5 Certification Exam consists of 60 questions that are to be completed in 90 minutes. H13-311_V3.5 exam covers a range of topics such as AI technologies, machine learning, deep learning, neural networks, natural language processing, computer vision, and more. H13-311_V3.5 exam is available in English and Chinese language, and the certification is valid for three years. Passing the exam indicates that the candidate has a good understanding of AI technologies, and is capable of designing, deploying and maintaining AI solutions using Huawei products and services.

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Huawei HCIA-AI V3.5 Sample Questions (Q28-Q33):

NEW QUESTION # 28
Grid search is a method of parameter adjustment.

  • A. TRUE
  • B. FALSE

Answer: B


NEW QUESTION # 29
After the data has completed the feature engineering operation, in the process of constructing the model, which of the following options is not a step in the decision tree construction process?

  • A. Pruning
  • B. Data cleaning
  • C. Feature selection
  • D. Decision tree generation

Answer: B


NEW QUESTION # 30
Vector group a1=(1, 1, 1), a2=(0,2.5), a3=(1.3,6), which of the following options is correct?

  • A. aHa2+a3=0
  • B. Linear independence
  • C. 2a1+a2+a3=0
  • D. Linear correlation

Answer: D


NEW QUESTION # 31
Which of the following statements about datasets are true?

  • A. In machine learning, a dataset is generally divided into a training set, validation set, and test set.
  • B. When it comes to the machine learning process, the validation set and the test set are essentially the same.
  • C. A dataset generally has multiple dimensions. In each dimension, events or attributes that reflect the performance or nature of a sample in a particular aspect are called features.
  • D. Testing refers to a process that uses a trained model for prediction. The dataset, which is used for testing, is called a testing set, and each sample is called a test sample.

Answer: A,C,D

Explanation:
In machine learning:
The testing set is a dataset used after training to evaluate the model's performance and generalization ability. Each sample in this set is called a test sample.
A dataset generally has multiple dimensions, with each dimension representing a feature or attribute of the data.
A typical machine learning process divides the data into a training set (to train the model), a validation set (to tune hyperparameters and avoid overfitting), and a test set (to evaluate the model's final performance).
The statement that the validation set and test set are the same is false because they serve different purposes: validation is for hyperparameter tuning, while testing is for final model evaluation.


NEW QUESTION # 32
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. False
  • B. True

Answer: B


NEW QUESTION # 33
......

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