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H13-311_V3.5 Latest Exam Materials - Exam H13-311_V3.5 Topics
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Huawei H13-311_V3.5 (HCIA-AI V3.5) Certification Exam is a globally recognized certification that is highly valued by employers. HCIA-AI V3.5 certification exam validates the candidate's knowledge and skills in implementing and managing AI technologies using Huawei's AI platform. HCIA-AI V3.5 certification exam is an excellent choice for professionals who want to demonstrate their expertise in AI technologies, enhance their career prospects, and stay ahead of the competition.
The H13-311_V3.5 Exam comprises various topics, including basic Python programming concepts, data manipulation, and visualization methods. It also covers more advanced topics such as building and deploying machine learning models using various algorithms. The curriculum of HCIA-AI V3.5 is comprehensive and covers a broad range of topics, making it an ideal certification for aspirants seeking recognition in this field.
Huawei HCIA-AI V3.5 Sample Questions (Q74-Q79):
NEW QUESTION # 74
TensorFlow2.0 The mechanism of graphs and conversations has been cancelled in.
- A. TRUE
- B. FALSE
Answer: B
NEW QUESTION # 75
Which of the following are the cloud services provided by Huawei Cloud El Visual Cognition?
(Multiple choice)
- A. Image processing
- B. Content detection
- C. Face recognition
- D. Text recognition
- E. Image recognition
Answer: A,B,C,D,E
NEW QUESTION # 76
Deep learning neural network training requires a lot of matrix calculations. Generally, we need to use hardware to enable the computer to have parallel computing capabilities. The following hardware devices can provide parallel computing capabilities.:
- A. CPU
- B. RAM
- C. GPU
- D. Motherboard
Answer: C
NEW QUESTION # 77
AI inference chips need to be optimized and are thus more complex than those used for training.
- A. TRUE
- B. FALSE
Answer: B
Explanation:
AI inference chips are generally simpler than training chips because inference involves running a trained model on new data, which requires fewer computations compared to the training phase. Training chips need to perform more complex tasks like backpropagation, gradient calculations, and frequent parameter updates. Inference, on the other hand, mostly involves forward pass computations, making inference chips optimized for speed and efficiency but not necessarily more complex than training chips.
Thus, the statement is false because inference chips are optimized for simpler tasks compared to training chips.
HCIA AI
Reference:
Cutting-edge AI Applications: Describes the difference between AI inference and training chips, focusing on their respective optimizations.
Deep Learning Overview: Explains the distinction between the processes of training and inference, and how hardware is optimized accordingly.
NEW QUESTION # 78
There are many commercial applications for machine learning services. What are the main business scenarios covered? (Multiple Choice)
- A. Telecom customer retention
- B. Retailer grouping
- C. Predictive maintenance
- D. Flnancial product recommendation
Answer: A,B,C,D
NEW QUESTION # 79
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