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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Deep Learning Fundamentals | 15% | - Training and Fine-tuning - Neural Network Basics - Optimization Algorithms - CNN and RNN Architectures |
| Topic 2: ModelArts Pro Development | 20% | - Hyperparameter Optimization - Model Deployment and Management - AutoML and Automatic Model Training - Inference Service Configuration |
| Topic 3: Natural Language Processing Application | 15% | - Text Classification Models - Text Preprocessing and Embedding - Language Model Fine-tuning - Named Entity Recognition |
| Topic 4: EI Model Development Fundamentals | 15% | - HiLens Framework and Skills - Development Environment Setup - EI Service and Architecture - Model Development Process |
| Topic 5: Image Recognition Application Development | 15% | - Image Segmentation - Object Detection Implementation - Image Classification Models - Transfer Learning with Pre-trained Models |
| Topic 6: HiLens Platform Development | 20% | - Skill Development Framework - Multi-modal Data Processing - Real-time Inference Optimization - Edge Deployment Strategy |
1. Huawei Cloud ModelArts is a one-stop AI development platform that supports multiple AI scenarios. Which of the following scenarios are supported by ModelArts?
A) Speech recognition
B) Image classification
C) Video analytics
D) Object detection
2. Overfitting is a condition where a model is overly simple and excessive generalization errors occur.
A) FALSE
B) TRUE
3. Vision transformer (ViT) performs well in image classification tasks. Which of the following is the main advantage of ViT?
A) It can handle small datasets with minimal labeling required.
B) The self-attention mechanism is used to capture global features of images, improving classification accuracy.
C) It can process high-resolution images to enhance classification accuracy.
D) It achieves fast convergence without using pre-trained models.
4. The objective of -------- is to extract and classify named entities in a text into pre-defined classes such as names, organizations, locations, time expressions, monetary values, and percentages. (Enter the abbreviation.)
5. Which of the following statements are true about the differences between using convolutional neural networks (CNNs) in text tasks and image tasks?
A) Color image input is multi-channel, whereas text input is single-channel.
B) For CNN, there is no difference in handling text or image tasks.
C) When the CNN is used for text tasks, the kernel size must be the same as the number of word vector dimensions. This constraint, however, does not apply to image tasks.
D) CNNs are suitable for image tasks, but they perform poorly in text tasks.
Solutions:
| Question # 1 Answer: A,B,C,D | Question # 2 Answer: A | Question # 3 Answer: B | Question # 4 Answer: Only visible for members | Question # 5 Answer: A,C |
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