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Huawei H13-321_V2.5 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Model Deployment and Operations | - Monitoring and Maintenance - Inference Services - Model Deployment Strategies |
| Huawei AI Ecosystem Tools | - AI Development Toolchain - MindSpore Framework Basics - Huawei Cloud AI Services |
| Data Processing | - Data Labeling and Preparation - Feature Engineering - Data Collection and Cleaning |
| Machine Learning | - Unsupervised Learning
|
| AI Application Development (EI) | - AI Service Integration - Building AI Applications - Enterprise Intelligence (EI) Concepts |
| AI Fundamentals | - Common AI Use Cases in Industry - AI Development Lifecycle - Introduction to Artificial Intelligence |
| Model Development with Huawei ModelArts | - ModelArts Platform Overview - AutoML Capabilities - Training Models on ModelArts |
| Deep Learning | - CNN and RNN Architectures - Model Training and Optimization - Neural Network Fundamentals |
Huawei HCIP-AI-EI Developer V2.5 Sample Questions:
When training a deep neural network model, a loss function measures the difference between the model's predictions and the actual labels.
- A. TRUE
- B. FALSE
Correct Answer: A 🗳️
Explanation: Only visible for Dumpexams members. You can sign-up / login (it's free).
Which of the following is not an acoustic feature of speech?
- A. Semantics
- B. Frequency
- C. Duration
- D. Amplitude
Correct Answer: A 🗳️
Explanation: Only visible for Dumpexams members. You can sign-up / login (it's free).
Which of the following ModelArts training parameters is used to customize hyperparameters?
- A. Algorithm Type
- B. Resource Pool
- C. Hyperparameter
- D. Compute Nodes
Correct Answer: C 🗳️
Explanation: Only visible for Dumpexams members. You can sign-up / login (it's free).
Which of the following statements about the multi-head attention mechanism of the Transformer are true?
- A. Each header's query, key, and value undergo a shared linear transformation to obtain them.
- B. The concatenated output is fed directly into the multi-headed attention mechanism.
- C. The multi-head attention mechanism captures information about different subspaces within a sequence.
- D. The dimension for each header is calculated by dividing the original embedded dimension by the number of headers before concatenation.
Correct Answer: C,D 🗳️
Maximum likelihood estimation (MLE) can be used for parameter estimation in a Gaussian mixture model (GMM).
- A. TRUE
- B. FALSE
Correct Answer: A 🗳️
Explanation: Only visible for Dumpexams members. You can sign-up / login (it's free).
