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Huawei H13-321_V2.0-ENU Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Speech Processing Lab Guide | 12% | - Huawei Cloud Speech Interaction Service - ModelArts speech application deployment - ASR and TTS service development |
| Topic 2: Natural Language Processing Theory and Applications | 10% | - BERT, GPT and pre-trained models - RNN, LSTM, GRU, Transformer architecture - Word representation and embedding - Text classification, NER, machine translation |
| Topic 3: Neural Network Basics | 4% | - Multilayer Perceptron (MLP) - Activation functions and regularization - Gradient descent and backpropagation - Basic concepts of neural networks |
| Topic 4: Overview of ModelArts | 4% | - Development environment and tool usage - Data processing, training, deployment capabilities - ModelArts platform positioning and architecture |
| Topic 5: Image Processing Theory and Applications | 26% | - Image processing fundamentals - Image classification, object detection, segmentation - Convolutional Neural Networks (CNN) - OCR and visual application development |
| Topic 6: Image Processing Lab Guide | 12% | - Ascend-based deployment - ModelArts-based image classification - Object detection and segmentation practice |
| Topic 7: Speech Processing Theory and Applications | 10% | - Automatic Speech Recognition (ASR) - Speech signal characteristics and processing - Acoustic and language modeling - Text-to-Speech (TTS) technology |
| Topic 8: Huawei AI Strategy and Full-Stack, All-Scenario AI Portfolio | 2% | - Full-stack and all-scenario AI technology layout - Huawei AI development strategy |
| Topic 9: Natural Language Processing Lab Guide | 10% | - Application integration and deployment - ModelArts NLP model training and tuning - Text classification and NER implementation |
Huawei HCIP-AI-EI Developer V2.0 Sample Questions:
Please match the following artificial intelligence algorithms and their corresponding fields
Reveal Solution Discussion 0Correct Answer:
AlphaGo (game decision making) DeepSpeech2 (speech recognition) BERT (reading comprehension) ResNet (image recognition)
Through image algorithms, the foreground and background of a person in a photo taken with an ordinary mobile phone are segmented, and then () operations are performed on () parts to achieve a blur effect similar to that of a SLR camera.
- A. Background, mean filter
- B. Foreground, median filter
- C. Foreground, mean filter
- D. Background, median filter
Correct Answer: A 🗳️
LSTM does not belong to the RNN network.
- A. False
- B. True
Correct Answer: A 🗳️
() in CANN combines the operator fusion of the internal storage architecture of the Ascend chip to reduce operator calling overhead and memory movement, and improve performance.
Reveal Solution Discussion 0Correct Answer:
Fusion engine
__________ is a deeply optimized general operator library provided by Huawei, which can meet the needs of most mainstream vision and NLP neural networks.
Reveal Solution Discussion 0Correct Answer:
CCE operator library
Myron -
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