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Huawei H13-321_V2.5 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| ModelArts Pro Development | 20% | - Inference Service Configuration - Hyperparameter Optimization - AutoML and Automatic Model Training - Model Deployment and Management |
| EI Model Development Fundamentals | 15% | - EI Service and Architecture - Development Environment Setup - HiLens Framework and Skills - Model Development Process |
| Image Recognition Application Development | 15% | - Transfer Learning with Pre-trained Models - Object Detection Implementation - Image Segmentation - Image Classification Models |
| HiLens Platform Development | 20% | - Edge Deployment Strategy - Real-time Inference Optimization - Skill Development Framework - Multi-modal Data Processing |
| Deep Learning Fundamentals | 15% | - Training and Fine-tuning - Optimization Algorithms - CNN and RNN Architectures - Neural Network Basics |
| Natural Language Processing Application | 15% | - Text Classification Models - Language Model Fine-tuning - Named Entity Recognition - Text Preprocessing and Embedding |
Huawei HCIP-AI-EI Developer V2.5 Sample Questions:
1. Among image preprocessing techniques, gamma correction is a common non-linear brightness adjustment method. Which of the following statements are true about the application and features of gamma correction?
A) Gamma correction is an enhancement technique based on exponential transformation mapping. It is used for non-linear contrast stretching.
B) When # > 1, the input low grayscale range is compressed, and the high grayscale range is stretched, enhancing the bright areas while compressing the dark areas.
C) When # < 1, the input high grayscale range is compressed, and the low grayscale range is stretched, enhancing the dark areas while compressing the bright areas.
D) Gamma correction applies only to grayscale images and does not apply to color images.
2. What are the advantages of deep learning-based speech recognition algorithms?
A) No data training
B) End-to-end task processing
C) Forced alignment of annotated data
D) Automated feature extraction
3. -------- is a text representation method based on the bag of words (BoW) model. It decomposes words into subwords and then adds the vector representations of the subwords to obtain word vectors, fully utilizing character N-gram information. (Fill in the blank.)
4. The accuracy of object location detection can be evaluated using the intersection over union (IoU) value, which is a ratio. The denominator is the overlapping area between the prediction bounding box and ground truth bounding box, and the numerator is the area of union encompassed by both boxes.
A) FALSE
B) TRUE
5. Which of the following methods are useful when tackling overfitting?
A) Using more complex models
B) Using dropout during model training
C) Data augmentation
D) Using parameter norm penalties
Solutions:
| Question # 1 Answer: A,B,C | Question # 2 Answer: B,D | Question # 3 Answer: Only visible for members | Question # 4 Answer: A | Question # 5 Answer: B,C,D |
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