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Huawei H13-321_V2.5 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: EI Model Development Fundamentals | 15% | - Model Development Process - Development Environment Setup - EI Service and Architecture - HiLens Framework and Skills |
| Topic 2: HiLens Platform Development | 20% | - Multi-modal Data Processing - Skill Development Framework - Edge Deployment Strategy - Real-time Inference Optimization |
| Topic 3: ModelArts Pro Development | 20% | - Hyperparameter Optimization - Model Deployment and Management - AutoML and Automatic Model Training - Inference Service Configuration |
| Topic 4: Image Recognition Application Development | 15% | - Object Detection Implementation - Image Classification Models - Image Segmentation - Transfer Learning with Pre-trained Models |
| Topic 5: Natural Language Processing Application | 15% | - Text Classification Models - Text Preprocessing and Embedding - Language Model Fine-tuning - Named Entity Recognition |
| Topic 6: Deep Learning Fundamentals | 15% | - Training and Fine-tuning - Optimization Algorithms - CNN and RNN Architectures - Neural Network Basics |
Huawei HCIP-AI-EI Developer V2.5 Sample Questions:
In 2017, the Google machine translation team proposed the Transformer in their paperAttention is All You Need. The Transformer consists of an encoder and a(n) --------. (Fill in the blank.)
Reveal Solution Discussion 0Correct Answer:
Decoder
Explanation:
The Transformer model architecture includes:
* Encoder:Encodes the input sequence into contextualized representations.
* Decoder:Uses the encoder output and self-attention over previously generated tokens to produce the target sequence.
Exact Extract from HCIP-AI EI Developer V2.5:
"The Transformer consists of an encoder-decoder structure, with self-attention mechanisms in both components for sequence-to-sequence learning." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: Transformer Overview
Which of the following statements about the levels of natural language understanding are true?
- A. Speech analysis involves distinguishing independent phonemes from a speech stream based on phoneme rules, and then identifying syllables and their lexemes or words according to the phoneme form rules.
- B. Pragmatic analysis is to study the influence of the language's external environment on the language users.
- C. Syntactic analysis is to find out the meaning of words, structural meaning, their combined meaning, so as to determine the true meaning or concept expressed by a language.
- D. Semantic analysis is to analyze the structure of sentences and phrases to find out the relationship between words and phrases, as well as their functions in sentences.
- E. Lexical analysis is to find the lexemes of a word and obtain linguistic information from them.
Correct Answer: A,B,E 🗳️
Explanation: Only visible for DumpStillValid 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. The concatenated output is fed directly into the multi-headed attention mechanism.
- B. The dimension for each header is calculated by dividing the original embedded dimension by the number of headers before concatenation.
- C. The multi-head attention mechanism captures information about different subspaces within a sequence.
- D. Each header's query, key, and value undergo a shared linear transformation to obtain them.
Correct Answer: B,C 🗳️
In an image preprocessing experiment, the cv2.imread("lena.png", 1) function provided by OpenCV is used to read images. The parameter "1" in this function represents a --------- -channel image. (Fill in the blank with a number.)
Reveal Solution Discussion 0Correct Answer:
3
Explanation:
In OpenCV:
* cv2.imread(filename, 1) reads the image incolor mode.
* This loads the image as a3-channelBGR image (Blue, Green, Red).
* Other modes: 0 for grayscale, -1 for unchanged (including alpha channel).
Exact Extract from HCIP-AI EI Developer V2.5:
"When the second parameter of cv2.imread is 1, the image is read in color mode, resulting in a 3-channel BGR image." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: Image Reading and Writing with OpenCV
Mel-frequency cepstral coefficients (MFCCs) take into account human auditory characteristics by first mapping the linear spectrum to the Mel nonlinear spectrum based on auditory perception, and then converting it to the cepstral domain.
- A. FALSE
- B. TRUE
Correct Answer: B 🗳️
Explanation: Only visible for DumpStillValid members. You can sign-up / login (it's free).
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