chore(i18n): sync translations with latest source changes (chunk 2/8, 133 changes)

translations/ja/.co-op-translator.json

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+    "original_hash": "8d9c5a4a7c7798d699672a22cb7fea86",
+    "translation_date": "2025-10-03T09:37:31+00:00",
+    "source_file": "troubleshoot.md",
+    "language_code": "zh-HK"
+  }
+}

translations/zh-HK/AGENTS.md

@@ -0,0 +1,317 @@
+# AGENTS.md
+
+## 項目概覽
+
+AI for Beginners 是一個全面的 12 週、24 節課程，涵蓋人工智能的基本知識。本教育資源庫包括使用 Jupyter Notebooks 的實踐課程、測驗以及動手實驗。課程內容包括：
+
+- 符號 AI：知識表示與專家系統
+- 神經網絡與深度學習：使用 TensorFlow 和 PyTorch
+- 計算機視覺技術與架構
+- 自然語言處理 (NLP)：包括 transformers 和 BERT
+- 專題：遺傳算法、強化學習、多代理系統
+- AI 倫理與負責任的 AI 原則
+
+**主要技術：** Python 3、Jupyter Notebooks、TensorFlow、PyTorch、Keras、OpenCV、Vue.js（用於測驗應用）
+
+**架構：** 教育內容資源庫，按主題區域組織 Jupyter Notebooks，並輔以基於 Vue.js 的測驗應用及廣泛的多語言支持。
+
+## 設置指令
+
+### 主要開發環境（Python/Jupyter）
+
+課程設計基於 Python 和 Jupyter Notebooks 運行。推薦使用 miniconda：
+
+```bash
+# Clone the repository
+git clone https://github.com/microsoft/ai-for-beginners
+cd ai-for-beginners
+
+# Create and activate conda environment
+conda env create --name ai4beg --file environment.yml
+conda activate ai4beg
+
+# Start Jupyter Notebook
+jupyter notebook
+# OR
+jupyter lab
+```
+
+### 替代方案：使用 devcontainer
+
+```bash
+# Open in VS Code and select "Reopen in Container" when prompted
+# The devcontainer will automatically set up the environment
+```
+
+### 測驗應用設置
+
+測驗應用是一個獨立的 Vue.js 應用，位於 `etc/quiz-app/`：
+
+```bash
+cd etc/quiz-app
+npm install
+npm run serve  # Development server
+npm run build  # Production build
+npm run lint   # Lint and fix files
+```
+
+## 開發工作流程
+
+### 使用 Jupyter Notebooks
+
+1. **本地開發：**
+   - 啟動 conda 環境：`conda activate ai4beg`
+   - 啟動 Jupyter：`jupyter notebook` 或 `jupyter lab`
+   - 導航到課程文件夾並打開 `.ipynb` 文件
+   - 交互式運行單元格以跟隨課程
+
+2. **VS Code 與 Python 擴展：**
+   - 在 VS Code 中打開資源庫
+   - 安裝 Python 擴展
+   - VS Code 會自動檢測並使用 conda 環境
+   - 直接在 VS Code 中打開 `.ipynb` 文件
+
+3. **雲端開發：**
+   - **GitHub Codespaces：** 點擊 "Code" → "Codespaces" → "Create codespace on main"
+   - **Binder：** 使用 README 中的 Binder 徽章在瀏覽器中啟動
+   - 注意：Binder 資源有限，且有一些網絡訪問限制
+
+### 高級課程的 GPU 支持
+
+後期課程顯著受益於 GPU 加速：
+
+- **Azure Data Science VM：** 使用支持 GPU 的 NC 系列虛擬機
+- **Azure Machine Learning：** 使用 GPU 計算的 notebook 功能
+- **Google Colab：** 單獨上傳 notebook（提供免費 GPU 支持）
+
+### 測驗應用開發
+
+```bash
+cd etc/quiz-app
+npm run serve  # Hot-reload development server at http://localhost:8080
+```
+
+## 測試說明
+
+這是一個以學習內容為重點的教育資源庫，而非傳統的軟件測試。沒有傳統的測試套件。
+
+### 驗證方法：
+
+1. **Jupyter Notebooks：** 按順序執行單元格以驗證代碼示例是否正常運行
+2. **測驗應用測試：** 通過開發服務器進行手動測試
+3. **翻譯驗證：** 檢查 `translations/` 文件夾中的翻譯內容
+4. **測驗應用代碼檢查：** 在 `etc/quiz-app/` 中運行 `npm run lint`
+
+### 運行代碼示例：
+
+```bash
+# Activate environment first
+conda activate ai4beg
+
+# Run Python scripts directly
+python lessons/4-ComputerVision/07-ConvNets/pytorchcv.py
+
+# Or execute notebooks
+jupyter notebook lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb
+```
+
+## 代碼風格
+
+### Python 代碼風格
+
+- 遵循標準 Python 規範，適合教育代碼
+- 清晰、易讀的代碼，優先考慮學習而非優化
+- 注釋解釋關鍵概念
+- 適合 Jupyter Notebook：單元格應盡可能自包含
+- 對課程內容無嚴格的代碼檢查要求
+
+### JavaScript/Vue.js（測驗應用）
+
+- ESLint 配置位於 `etc/quiz-app/package.json`
+- 運行 `npm run lint` 檢查並自動修復問題
+- Vue 2.x 規範
+- 基於組件的架構
+
+### 文件組織
+
+```
+lessons/
+  ├── 0-course-setup/          # Setup instructions
+  ├── 1-Intro/                 # Introduction to AI
+  ├── 2-Symbolic/              # Symbolic AI
+  ├── 3-NeuralNetworks/        # Neural Networks basics
+  ├── 4-ComputerVision/        # Computer Vision
+  ├── 5-NLP/                   # Natural Language Processing
+  ├── 6-Other/                 # Other AI techniques
+  ├── 7-Ethics/                # AI Ethics
+  └── X-Extras/                # Additional content
+
+etc/
+  ├── quiz-app/                # Vue.js quiz application
+  └── quiz-src/                # Quiz source files
+
+translations/                  # Multi-language translations
+```
+
+## 構建與部署
+
+### Jupyter 內容
+
+不需要構建過程 - Jupyter Notebooks 可直接執行。
+
+### 測驗應用
+
+```bash
+cd etc/quiz-app
+
+# Development
+npm run serve
+
+# Production build
+npm run build  # Outputs to etc/quiz-app/dist/
+
+# Deploy to Azure Static Web Apps
+# Azure automatically creates GitHub Actions workflow
+# See etc/quiz-app/README.md for detailed deployment instructions
+```
+
+### 文檔網站
+
+資源庫使用 Docsify 進行文檔管理：
+- `index.html` 作為入口點
+- 不需要構建 - 直接通過 GitHub Pages 提供服務
+- 訪問地址：https://microsoft.github.io/AI-For-Beginners/
+
+## 貢獻指南
+
+### 拉取請求流程
+
+1. **標題格式：** 清晰、描述性的標題，說明更改內容
+2. **CLA 要求：** 必須簽署 Microsoft CLA（自動檢查）
+3. **內容指南：**
+   - 保持教育重點和適合初學者的方式
+   - 測試所有 notebook 中的代碼示例
+   - 確保 notebook 從頭到尾正常運行
+   - 如果修改英文內容，請更新翻譯
+4. **測驗應用更改：** 提交前運行 `npm run lint`
+
+### 翻譯貢獻
+
+- 翻譯通過 GitHub Actions 使用 co-op-translator 自動完成
+- 手動翻譯存放於 `translations/<language-code>/`
+- 測驗翻譯存放於 `etc/quiz-app/src/assets/translations/`
+- 支持語言：40+ 種語言（完整列表見 README）
+
+### 活躍貢獻領域
+
+請參閱 `etc/CONTRIBUTING.md` 了解當前需求：
+- 深度強化學習部分
+- 物體檢測改進
+- 命名實體識別示例
+- 自定義嵌入訓練樣本
+
+## 環境配置
+
+### 必需依賴項
+
+```bash
+# Core Python packages (from requirements.txt)
+tensorflow==2.17.0
+torch (via conda)
+torchvision (via conda)
+keras==3.5.0
+opencv (via conda)
+scikit-learn
+numpy==1.26
+pandas==2.2.2
+matplotlib==3.9
+jupyter
+```
+
+### 環境變量
+
+基本使用不需要特殊環境變量。
+
+對於 Azure 部署（測驗應用）：
+- `AZURE_STATIC_WEB_APPS_API_TOKEN`（由 Azure 自動設置）
+
+## 調試與故障排除
+
+### 常見問題
+
+**問題：** Conda 環境創建失敗
+- **解決方案：** 首先更新 conda：`conda update conda -y`
+- 確保磁盤空間充足（建議 50GB）
+
+**問題：** Jupyter kernel 未找到
+- **解決方案：**
+  ```bash
+  conda activate ai4beg
+  python -m ipykernel install --user --name ai4beg
+  ```
+
+**問題：** Notebook 中未檢測到 GPU
+- **解決方案：**
+  - 驗證 CUDA 安裝：`nvidia-smi`
+  - 檢查 PyTorch GPU：`python -c "import torch; print(torch.cuda.is_available())"`
+  - 檢查 TensorFlow GPU：`python -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"`
+
+**問題：** 測驗應用無法啟動
+- **解決方案：**
+  ```bash
+  cd etc/quiz-app
+  rm -rf node_modules package-lock.json
+  npm install
+  npm run serve
+  ```
+
+**問題：** Binder 超時或阻止下載
+- **解決方案：** 使用 GitHub Codespaces 或本地設置以獲得更好的資源訪問
+
+### 記憶體問題
+
+某些課程需要大量 RAM（建議 8GB+）：
+- 對於資源密集型課程，使用雲端虛擬機
+- 在訓練模型時關閉其他應用
+- 如果內存不足，減少 notebook 中的批量大小
+
+## 附加說明
+
+### 對課程講師的建議
+
+- 請參閱 `lessons/0-course-setup/for-teachers.md` 獲取教學指導
+- 課程是自包含的，可以按順序教授或單獨選擇
+- 預估時間：12 週，每週 2 節課
+
+### 雲端資源
+
+- **Azure for Students：** 學生可獲得免費額度
+- **Microsoft Learn：** 課程中鏈接的補充學習路徑
+- **Binder：** 免費但資源有限，且有一些網絡限制
+
+### 代碼執行選項
+
+1. **本地（推薦）：** 完全控制，最佳性能，支持 GPU
+2. **GitHub Codespaces：** 基於雲端的 VS Code，適合快速訪問
+3. **Binder：** 基於瀏覽器的 Jupyter，免費但有限
+4. **Azure ML Notebooks：** 企業選項，支持 GPU
+5. **Google Colab：** 單獨上傳 notebook，提供免費 GPU 層
+
+### 使用 Notebook
+
+- Notebook 設計為逐個單元格運行以便學習
+- 許多 notebook 在首次運行時下載數據集（可能需要一些時間）
+- 某些模型需要 GPU 才能有合理的訓練時間
+- 儘可能使用預訓練模型以減少計算需求
+
+### 性能考量
+
+- 後期計算機視覺課程（CNNs、GANs）受益於 GPU
+- NLP transformer 課程可能需要大量 RAM
+- 從零開始訓練具有教育意義但耗時
+- 遷移學習示例可減少訓練時間
+
+---
+
+**免責聲明**：  
+此文件已使用人工智能翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。應以原始語言的文件作為權威來源。對於關鍵資訊，建議尋求專業的人工作業翻譯。我們對因使用此翻譯而引起的任何誤解或錯誤詮釋概不負責。

translations/zh-HK/README.md

@@ -0,0 +1,224 @@
+[![GitHub license](https://img.shields.io/github/license/microsoft/AI-For-Beginners.svg)](https://github.com/microsoft/AI-For-Beginners/blob/main/LICENSE)
+[![GitHub contributors](https://img.shields.io/github/contributors/microsoft/AI-For-Beginners.svg)](https://GitHub.com/microsoft/AI-For-Beginners/graphs/contributors/)
+[![GitHub issues](https://img.shields.io/github/issues/microsoft/AI-For-Beginners.svg)](https://GitHub.com/microsoft/AI-For-Beginners/issues/)
+[![GitHub pull-requests](https://img.shields.io/github/issues-pr/microsoft/AI-For-Beginners.svg)](https://GitHub.com/microsoft/AI-For-Beginners/pulls/)
+[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com)
+
+[![GitHub watchers](https://img.shields.io/github/watchers/microsoft/AI-For-Beginners.svg?style=social&label=Watch)](https://GitHub.com/microsoft/AI-For-Beginners/watchers/)
+[![GitHub forks](https://img.shields.io/github/forks/microsoft/AI-For-Beginners.svg?style=social&label=Fork)](https://GitHub.com/microsoft/AI-For-Beginners/network/)
+[![GitHub stars](https://img.shields.io/github/stars/microsoft/AI-For-Beginners.svg?style=social&label=Star)](https://GitHub.com/microsoft/AI-For-Beginners/stargazers/)
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/microsoft/ai-for-beginners/HEAD)
+[![Gitter](https://badges.gitter.im/Microsoft/ai-for-beginners.svg)](https://gitter.im/Microsoft/ai-for-beginners?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
+
+[![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG)
+
+# 人工智能初學者課程
+
+|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/zh-HK/ai-overview.0857791951d19500.webp)|
+|:---:|
+| AI For Beginners - _手繪筆記由 [@girlie_mac](https://twitter.com/girlie_mac) 製作_ |
+
+探索 **人工智能**（AI）的世界，透過我們為期12週、共24課的課程！課程包含實用的課堂內容、測驗及實驗室練習。該課程適合初學者，涵蓋如 TensorFlow 和 PyTorch 等工具，以及 AI 倫理論述。
+
+### 🌐 多語言支援
+
+#### 透過 GitHub Action 支援（自動且隨時更新）
+
+<!-- CO-OP TRANSLATOR LANGUAGES TABLE START -->
+[阿拉伯語](../ar/README.md) | [孟加拉語](../bn/README.md) | [保加利亞語](../bg/README.md) | [緬甸語 (緬甸)](../my/README.md) | [中文（簡體）](../zh-CN/README.md) | [中文（繁體，香港）](./README.md) | [中文（繁體，澳門）](../zh-MO/README.md) | [中文（繁體，台灣）](../zh-TW/README.md) | [克羅地亞語](../hr/README.md) | [捷克語](../cs/README.md) | [丹麥語](../da/README.md) | [荷蘭語](../nl/README.md) | [愛沙尼亞語](../et/README.md) | [芬蘭語](../fi/README.md) | [法語](../fr/README.md) | [德語](../de/README.md) | [希臘語](../el/README.md) | [希伯來語](../he/README.md) | [印地語](../hi/README.md) | [匈牙利語](../hu/README.md) | [印度尼西亞語](../id/README.md) | [意大利語](../it/README.md) | [日語](../ja/README.md) | [卡納達語](../kn/README.md) | [韓語](../ko/README.md) | [立陶宛語](../lt/README.md) | [馬來語](../ms/README.md) | [馬拉雅拉姆語](../ml/README.md) | [馬拉地語](../mr/README.md) | [尼泊爾語](../ne/README.md) | [奈及利亞皮欽語](../pcm/README.md) | [挪威語](../no/README.md) | [波斯語 (法爾西語)](../fa/README.md) | [波蘭語](../pl/README.md) | [巴西葡萄牙語](../pt-BR/README.md) | [葡萄牙語 (葡萄牙)](../pt-PT/README.md) | [旁遮普語 (古魯穆奇文)](../pa/README.md) | [羅馬尼亞語](../ro/README.md) | [俄語](../ru/README.md) | [塞爾維亞語 (西里爾字母)](../sr/README.md) | [斯洛伐克語](../sk/README.md) | [斯洛文尼亞語](../sl/README.md) | [西班牙語](../es/README.md) | [斯瓦希里語](../sw/README.md) | [瑞典語](../sv/README.md) | [他加祿語 (菲律賓語)](../tl/README.md) | [泰米爾語](../ta/README.md) | [泰盧固語](../te/README.md) | [泰語](../th/README.md) | [土耳其語](../tr/README.md) | [烏克蘭語](../uk/README.md) | [烏爾都語](../ur/README.md) | [越南語](../vi/README.md)
+
+> **想要本地克隆？**
+
+> 本存儲庫包含50多種語言翻譯，大幅增加下載大小。若想不含翻譯文件克隆，請使用稀疏簽出：
+> ```bash
+> git clone --filter=blob:none --sparse https://github.com/microsoft/AI-For-Beginners.git
+> cd AI-For-Beginners
+> git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'
+> ```
+> 這會讓您以更快速度下載並取得完成課程所需的全部內容。
+<!-- CO-OP TRANSLATOR LANGUAGES TABLE END -->
+
+**若想新增其他翻譯語言，支援的語言列表請見 [這裡](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
+
+## 加入社群
+[![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG)
+
+## 你將學到什麼
+
+**[課程思維導圖](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
+
+在此課程中，你將學習：
+
+* 不同的人工智能方法，包括「舊派」的符號方法，具備 **知識表示** 與推理 ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))。
+* **神經網絡** 與 **深度學習**，現代 AI 的核心。課程將透過兩大熱門框架 [TensorFlow](http://Tensorflow.org) 與 [PyTorch](http://pytorch.org) 以程式碼說明其背後概念。
+* 用以處理影像與文字的 **神經架構**。涵蓋近年模型，但在最新技術面可能略有不足。
+* 少部分較少人知的 AI 方法，例如 **遺傳算法** 與 **多智能體系統**。
+
+本課程不包含：
+
+> [在我們的 Microsoft Learn 集合中，找到本課程的所有額外資源](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
+
+* **AI 在商業中的應用案例**。建議參考 Microsoft Learn 上的 [商業用戶人工智能入門](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) 學習路徑，或與 [INSEAD](https://www.insead.edu/) 合作開發的 [AI 商學院](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)。
+* **經典機器學習**，可參閱我們的 [初學者機器學習課程](http://github.com/Microsoft/ML-for-Beginners)。
+* 使用 **[認知服務](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** 所建置的實用 AI 應用。建議從 Microsoft Learn 的 [視覺](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)、[自然語言處理](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum) 及 **[Azure OpenAI 服務的生成式 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 等模組開始。
+* 特定的機器學習 **雲端框架**，例如 [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)、[Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum)、或 [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)。可以參考 [使用 Azure Machine Learning 建置與運作機器學習解決方案](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) 及 [使用 Azure Databricks 建置與運作機器學習解決方案](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) 學習路徑。
+* **對話式 AI** 與 **聊天機器人**。有單獨的 [建立對話式 AI 解決方案](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) 學習路徑，也可參考 [這篇博客文章](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) 獲取更多細節。
+* 深入的深度學習 **數學原理**。推薦閱讀 Ian Goodfellow、Yoshua Bengio 和 Aaron Courville 所著的 [深度學習](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)（線上版本亦可在 [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) 瀏覽）。
+
+對於想輕鬆了解 _雲端 AI_ 主題者，建議參考 [Azure 上的人工智能入門](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) 學習路徑。
+
+# 內容
+
+|     |                                                                 課程連結                                                                  |                                           PyTorch/Keras/TensorFlow                                          | 實驗室                                                            |
+| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
+| 0  |                                 [課程安裝](./lessons/0-course-setup/setup.md)                                 |                      [設定你的開發環境](./lessons/0-course-setup/how-to-run.md)                       |   |
+| I  |               [**人工智能簡介**](./lessons/1-Intro/README.md)      | | |
+| 01  |       [人工智能的介紹與歷史](./lessons/1-Intro/README.md)       |           -                            | -  |
+| II |              **符號型 AI**              |
+| 02  |       [知識表示與專家系統](./lessons/2-Symbolic/README.md)       |            [專家系統](./lessons/2-Symbolic/Animals.ipynb) /  [本體論](./lessons/2-Symbolic/FamilyOntology.ipynb) /[概念圖](./lessons/2-Symbolic/MSConceptGraph.ipynb)                             |  |
+| III |                        [**神經網絡簡介**](./lessons/3-NeuralNetworks/README.md) |||
+| 03  |                [感知器](./lessons/3-NeuralNetworks/03-Perceptron/README.md)                 |                       [筆記本](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb)                      | [實驗室](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
+| 04  |                   [多層感知器及建立我們自己的框架](./lessons/3-NeuralNetworks/04-OwnFramework/README.md)                   |        [筆記本](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb)        | [實驗室](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
+| 05  |            [框架入門（PyTorch/TensorFlow）及過度擬合](./lessons/3-NeuralNetworks/05-Frameworks/README.md)             |           [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb)             | [實驗室](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
+| IV  |            [**電腦視覺**](./lessons/4-ComputerVision/README.md)             | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [在 Microsoft Azure 探索電腦視覺](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
+| 06  |            [電腦視覺入門。OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md)             |           [筆記本](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb)         | [實驗室](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
+| 07  |            [卷積神經網絡](./lessons/4-ComputerVision/07-ConvNets/README.md) &  [CNN 架構](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md)             |           [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb)             | [實驗室](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
+| 08  |            [預訓練網絡與遷移學習](./lessons/4-ComputerVision/08-TransferLearning/README.md) 及 [訓練技巧](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md)             |           [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb)             | [實驗室](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
+| 09  |            [自編碼器和變分自編碼器](./lessons/4-ComputerVision/09-Autoencoders/README.md)             |           [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb)             |  |
+| 10  |            [生成對抗網絡與藝術風格遷移](./lessons/4-ComputerVision/10-GANs/README.md)             |           [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb)             |  |
+| 11  |            [目標檢測](./lessons/4-ComputerVision/11-ObjectDetection/README.md)             |         [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb)             | [實驗室](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
+| 12  |            [語意分割。U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md)             |           [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb)             |  |
+| V  |            [**自然語言處理**](./lessons/5-NLP/README.md)             | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [在 Microsoft Azure 探索自然語言處理](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
+| 13  |            [文本表示。詞袋模型/TF-IDF](./lessons/5-NLP/13-TextRep/README.md)             |           [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb)             | |
+| 14  |            [語意詞嵌入。Word2Vec 和 GloVe](./lessons/5-NLP/14-Embeddings/README.md)             |           [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb)             |  |
+| 15  |            [語言建模。訓練你自己的嵌入](./lessons/5-NLP/15-LanguageModeling/README.md)             |           [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb)             | [實驗室](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
+| 16  |            [循環神經網絡](./lessons/5-NLP/16-RNN/README.md)             |           [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb)             |  |
+| 17  |            [生成循環網絡](./lessons/5-NLP/17-GenerativeNetworks/README.md)             |           [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb)             | [實驗室](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
+| 18  |            [變壓器。BERT。](./lessons/5-NLP/18-Transformers/README.md)             |           [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb)             |  |
+| 19  |            [命名實體識別](./lessons/5-NLP/19-NER/README.md)             |           [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb)             | [實驗室](./lessons/5-NLP/19-NER/lab/README.md) |
+| 20  |            [大型語言模型、提示編程與少量示例任務](./lessons/5-NLP/20-LangModels/README.md)             |           [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
+| VI |            **其他 AI 技術** || |
+| 21  |            [遺傳算法](./lessons/6-Other/21-GeneticAlgorithms/README.md)             |           [筆記本](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
+| 22  |            [深度強化學習](./lessons/6-Other/22-DeepRL/README.md)             |           [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb)             | [實驗室](./lessons/6-Other/22-DeepRL/lab/README.md) |
+| 23  |            [多智能體系統](./lessons/6-Other/23-MultiagentSystems/README.md)             |  | |
+| VII |            **AI 倫理** | | |
+| 24  |            [AI 倫理與負責任的 AI](./lessons/7-Ethics/README.md)             |           [Microsoft Learn: 負責任的 AI 原則](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
+| IX  |            **額外資源** | | |
+| 25  |            [多模態網絡、CLIP 和 VQGAN](./lessons/X-Extras/X1-MultiModal/README.md)             |           [筆記本](./lessons/X-Extras/X1-MultiModal/Clip.ipynb)    | |
+
+## 每課包含
+
+* 預習材料
+* 可執行的 Jupyter 筆記本，通常針對特定框架（**PyTorch** 或 **TensorFlow**）。可執行的筆記本同時包含很多理論內容，因此想要理解主題，至少需要通讀一個版本的筆記本（PyTorch 或 TensorFlow 版本）。
+* 某些主題提供 **實驗室**，讓你有機會嘗試將學到的知識運用到具體問題中。
+* 部分章節包含連結至涵蓋相關內容的 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 模組。
+
+## 入門指南
+
+### 🎯 你是 AI 新手嗎？從這裡開始！
+
+如果你完全沒有 AI 經驗，想快速獲得實戰範例，請查看我們的 [**新手友好範例**](./examples/README.md)！內容包括：
+
+- 🌟 **Hello AI World** - 你的第一個 AI 程式（模式識別）
+- 🧠 **簡單的神經網絡** - 從零構建神經網絡  
+
+- 🖼️ **影像分類器** - 使用詳細註解來分類影像  
+- 💬 **文字情感分析** - 分析文字的正面/負面情感  
+
+這些範例旨在幫助你在深入完整課程之前，先瞭解 AI 概念。
+
+### 📚 完整課程設定
+
+- 我們建立了一個[設定課程](./lessons/0-course-setup/setup.md)來幫助你設定開發環境。 - 教育工作者也有為你們準備的[課程設定課程](./lessons/0-course-setup/for-teachers.md)！  
+- 如何[在 VSCode 或 Codespace 中執行程式碼](./lessons/0-course-setup/how-to-run.md)  
+
+請依照以下步驟操作：
+
+Fork 倉庫：點擊此頁面右上角的「Fork」按鈕。
+
+Clone 倉庫：`git clone https://github.com/microsoft/AI-For-Beginners.git`
+
+別忘了為此倉庫加星 (🌟)，之後比較容易找到它。
+
+## 認識其他學習者
+
+加入我們的[官方 AI Discord 伺服器](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum)，與其他正在學習本課程的學員交流並取得支援。
+
+如果你在開發中有產品回饋或疑問，請造訪我們的[Azure AI Foundry 開發者論壇](https://aka.ms/foundry/forum)
+
+## 測驗
+
+> **關於測驗的說明**：所有測驗內容都包含在 etc\quiz-app 的 Quiz-app 資料夾中，或是可[線上使用](https://ff-quizzes.netlify.app/)。這些測驗從課程中連結，可在本機執行測驗應用程式，或部署到 Azure；請依照 `quiz-app` 資料夾中的說明操作。測驗內容正逐步本地化。
+
+## 需要協助
+
+你有建議或發現拼寫或程式碼錯誤嗎？歡迎提出議題或建立拉取請求。
+
+## 特別感謝
+
+* **✍️ 主要作者:** [Dmitry Soshnikov](http://soshnikov.com), PhD  
+* **🔥 編輯:** [Jen Looper](https://twitter.com/jenlooper), PhD  
+* **🎨 筆記插畫師:** [Tomomi Imura](https://twitter.com/girlie_mac)  
+* **✅ 測驗題目創建者:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)  
+* **🙏 核心貢獻者:** [Evgenii Pishchik](https://github.com/Pe4enIks)  
+
+## 其他課程
+
+我們團隊也製作其他課程！請參閱：
+
+<!-- CO-OP TRANSLATOR OTHER COURSES START -->
+### LangChain
+[![LangChain4j for Beginners](https://img.shields.io/badge/LangChain4j%20for%20Beginners-22C55E?style=for-the-badge&&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchain4j-for-beginners)
+[![LangChain.js for Beginners](https://img.shields.io/badge/LangChain.js%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin)
+
+---
+
+### Azure / Edge / MCP / Agents
+[![AZD for Beginners](https://img.shields.io/badge/AZD%20for%20Beginners-0078D4?style=for-the-badge&labelColor=E5E7EB&color=0078D4)](https://github.com/microsoft/AZD-for-beginners?WT.mc_id=academic-105485-koreyst)
+[![Edge AI for Beginners](https://img.shields.io/badge/Edge%20AI%20for%20Beginners-00B8E4?style=for-the-badge&labelColor=E5E7EB&color=00B8E4)](https://github.com/microsoft/edgeai-for-beginners?WT.mc_id=academic-105485-koreyst)
+[![MCP for Beginners](https://img.shields.io/badge/MCP%20for%20Beginners-009688?style=for-the-badge&labelColor=E5E7EB&color=009688)](https://github.com/microsoft/mcp-for-beginners?WT.mc_id=academic-105485-koreyst)
+[![AI Agents for Beginners](https://img.shields.io/badge/AI%20Agents%20for%20Beginners-00C49A?style=for-the-badge&labelColor=E5E7EB&color=00C49A)](https://github.com/microsoft/ai-agents-for-beginners?WT.mc_id=academic-105485-koreyst)
+
+---
+
+### 生成式 AI 系列
+[![Generative AI for Beginners](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst)
+[![Generative AI (.NET)](https://img.shields.io/badge/Generative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst)
+[![Generative AI (Java)](https://img.shields.io/badge/Generative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst)
+[![Generative AI (JavaScript)](https://img.shields.io/badge/Generative%20AI%20(JavaScript)-E879F9?style=for-the-badge&labelColor=E5E7EB&color=E879F9)](https://github.com/microsoft/generative-ai-with-javascript?WT.mc_id=academic-105485-koreyst)
+
+---
+
+### 核心學習
+[![ML for Beginners](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst)
+[![Data Science for Beginners](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst)
+[![AI for Beginners](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst)
+[![Cybersecurity for Beginners](https://img.shields.io/badge/Cybersecurity%20for%20Beginners-F97316?style=for-the-badge&labelColor=E5E7EB&color=F97316)](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung)
+[![Web Dev for Beginners](https://img.shields.io/badge/Web%20Dev%20for%20Beginners-EC4899?style=for-the-badge&labelColor=E5E7EB&color=EC4899)](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst)
+[![IoT for Beginners](https://img.shields.io/badge/IoT%20for%20Beginners-14B8A6?style=for-the-badge&labelColor=E5E7EB&color=14B8A6)](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst)
+[![XR Development for Beginners](https://img.shields.io/badge/XR%20Development%20for%20Beginners-38BDF8?style=for-the-badge&labelColor=E5E7EB&color=38BDF8)](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst)
+
+---
+
+### Copilot 系列
+[![Copilot for AI Paired Programming](https://img.shields.io/badge/Copilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst)
+[![Copilot for C#/.NET](https://img.shields.io/badge/Copilot%20for%20C%23/.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst)
+[![Copilot Adventure](https://img.shields.io/badge/Copilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst)
+<!-- CO-OP TRANSLATOR OTHER COURSES END -->
+
+## 尋求協助
+
+如果你在開發 AI 應用程式時遇到困難或有任何問題，可加入學習者與經驗開發者共聚的 MCP 討論，這是一個充滿支援的社群，歡迎提問並自由分享知識。
+
+[![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG)
+
+如果你在開發中有產品回饋或錯誤，請造訪：
+
+[![Microsoft Foundry Developer Forum](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum)
+
+---
+
+<!-- CO-OP TRANSLATOR DISCLAIMER START -->
+**免責聲明**：  
+本文件乃使用人工智能翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 所翻譯。雖然我們致力於確保準確性，但請注意自動翻譯可能包含錯誤或不準確之處。原始文件的本地語言版本應被視為權威來源。對於重要資訊，建議採用專業人工翻譯。我們不對因使用本翻譯所引致的任何誤解或誤釋負責。
+<!-- CO-OP TRANSLATOR DISCLAIMER END -->

translations/zh-HK/SECURITY.md

@@ -0,0 +1,40 @@
+## 安全性
+
+Microsoft 非常重視我們軟件產品和服務的安全性，包括透過我們的 GitHub 組織管理的所有原始碼庫，這些組織包括 [Microsoft](https://github.com/Microsoft)、[Azure](https://github.com/Azure)、[DotNet](https://github.com/dotnet)、[AspNet](https://github.com/aspnet)、[Xamarin](https://github.com/xamarin) 和 [我們的 GitHub 組織](https://opensource.microsoft.com/)。
+
+如果您認為在任何 Microsoft 擁有的原始碼庫中發現了符合 [Microsoft 安全漏洞定義](https://aka.ms/opensource/security/definition) 的安全漏洞，請按照以下說明向我們報告。
+
+## 報告安全問題
+
+**請勿透過公開的 GitHub 問題報告安全漏洞。**
+
+相反，請透過 Microsoft 安全響應中心 (MSRC) 報告，網址為 [https://msrc.microsoft.com/create-report](https://aka.ms/opensource/security/create-report)。
+
+如果您希望在不登入的情況下提交報告，請發送電子郵件至 [secure@microsoft.com](mailto:secure@microsoft.com)。如果可能，請使用我們的 PGP 密鑰加密您的訊息；您可以從 [Microsoft 安全響應中心 PGP 密鑰頁面](https://aka.ms/opensource/security/pgpkey) 下載密鑰。
+
+您應在 24 小時內收到回覆。如果因某些原因未收到回覆，請透過電子郵件跟進，以確保我們收到您的原始訊息。更多資訊可參考 [microsoft.com/msrc](https://aka.ms/opensource/security/msrc)。
+
+請提供以下所需資訊（盡可能提供完整），以幫助我們更好地了解問題的性質和範圍：
+
+  * 問題類型（例如：緩衝區溢出、SQL 注入、跨站腳本攻擊等）
+  * 與問題相關的原始碼文件的完整路徑
+  * 受影響原始碼的位置（標籤/分支/提交或直接 URL）
+  * 重現問題所需的任何特殊配置
+  * 重現問題的逐步指引
+  * 概念驗證或漏洞利用代碼（如果可能）
+  * 問題的影響，包括攻擊者可能如何利用該問題
+
+這些資訊將幫助我們更快速地處理您的報告。
+
+如果您是為漏洞賞金計劃報告，提供更完整的報告可能會獲得更高的賞金獎勵。請訪問我們的 [Microsoft 漏洞賞金計劃](https://aka.ms/opensource/security/bounty) 頁面，了解更多有關我們現行計劃的詳情。
+
+## 優先語言
+
+我們偏好所有溝通使用英文。
+
+## 政策
+
+Microsoft 遵循 [協調漏洞披露](https://aka.ms/opensource/security/cvd) 的原則。
+
+**免責聲明**：  
+本文件已使用人工智能翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。應以原文文件作為權威來源。對於關鍵資訊，建議尋求專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或錯誤解釋概不負責。

translations/zh-HK/etc/CODE_OF_CONDUCT.md

@@ -0,0 +1,12 @@
+# Microsoft 開源行為準則
+
+此項目已採用 [Microsoft 開源行為準則](https://opensource.microsoft.com/codeofconduct/)。
+
+資源：
+
+- [Microsoft 開源行為準則](https://opensource.microsoft.com/codeofconduct/)
+- [Microsoft 行為準則常見問題](https://opensource.microsoft.com/codeofconduct/faq/)
+- 如有疑問或關注，請聯絡 [opencode@microsoft.com](mailto:opencode@microsoft.com)
+
+**免責聲明**：  
+本文件已使用人工智能翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。應以原文文件作為權威來源。如涉及關鍵資訊，建議尋求專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或誤釋不承擔責任。

translations/zh-HK/etc/CONTRIBUTING.md

@@ -0,0 +1,20 @@
+# 貢獻指南
+
+此項目歡迎各種貢獻和建議。大多數貢獻需要您同意一份貢獻者許可協議 (CLA)，聲明您擁有權利並實際授予我們使用您貢獻的權利。詳情請訪問 https://cla.microsoft.com。
+
+當您提交拉取請求時，CLA 機器人會自動判斷您是否需要提供 CLA，並適當地標記 PR（例如，添加標籤或評論）。只需按照機器人提供的指示操作即可。您只需在所有使用我們 CLA 的倉庫中完成一次此操作。
+
+此項目採用了 [Microsoft 開源行為準則](https://opensource.microsoft.com/codeofconduct/)。如需更多資訊，請參閱 [行為準則常見問題](https://opensource.microsoft.com/codeofconduct/faq/) 或聯繫 [opencode@microsoft.com](mailto:opencode@microsoft.com) 提出其他問題或意見。
+
+# 尋求貢獻
+
+我們目前正在積極尋求以下主題的貢獻：
+
+- [ ] 撰寫有關深度強化學習的章節
+- [ ] 改進物件檢測的章節和筆記本
+- [ ] PyTorch Lightning（針對[此章節](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/05-Frameworks/README.md)）
+- [ ] 撰寫有關命名實體識別的章節和範例
+- [ ] 為[此章節](https://github.com/microsoft/AI-For-Beginners/tree/main/5-NLP/15-LanguageModeling) 創建訓練自定義嵌入的範例
+
+**免責聲明**：  
+本文件使用人工智能翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。應以原文文件作為權威來源。對於關鍵資訊，建議尋求專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或誤釋不承擔責任。

translations/zh-HK/etc/Mindmap.md

@@ -0,0 +1,78 @@
+# 人工智能
+
+## [人工智能簡介](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/1-Intro/README.md)
+ - 人工智能的定義
+ - 人工智能的歷史
+ - 人工智能的方法
+     - 自上而下/符號式
+     - 自下而上/神經網絡
+     - 演化式
+     - 協同/湧現式人工智能
+ - [Microsoft AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-cacaste)
+
+## [符號式人工智能](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/2-Symbolic/README.md)
+ - 知識表示
+ - [專家系統](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/2-Symbolic/Animals.ipynb)
+ - [本體論](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/2-Symbolic/FamilyOntology.ipynb)
+ - 語義網
+
+## [神經網絡](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/3-NeuralNetworks/README.md)
+ - [感知器](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/3-NeuralNetworks/03-Perceptron/README.md)
+ - [多層網絡](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/3-NeuralNetworks/04-OwnFramework/README.md)
+ - [框架簡介](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/3-NeuralNetworks/05-Frameworks/README.md)
+   - [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb)
+   - [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.md)
+   - [過擬合](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/3-NeuralNetworks/05-Frameworks/Overfitting.md)
+
+## [計算機視覺](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/README.md)
+ - 在 Microsoft Learn 上
+    - [人工智能基礎：探索計算機視覺](https://docs.microsoft.com/learn/paths/explore-computer-vision-microsoft-azure/?WT.mc_id=academic-77998-cacaste)
+    - [使用 PyTorch 的計算機視覺](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste)
+    - [使用 TensorFlow 的計算機視覺](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)
+ - [計算機視覺簡介：OpenCV](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/06-IntroCV/README.md)
+ - [卷積網絡](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/07-ConvNets/README.md)
+   - [卷積神經網絡架構](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md)
+ - [遷移學習](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/08-TransferLearning/README.md)
+   - [訓練技巧](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md)
+ - [自編碼器和變分自編碼器](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/09-Autoencoders/README.md)
+ - [生成對抗網絡](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/10-GANs/README.md)
+ - [風格遷移](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/10-GANs/StyleTransfer.ipynb)
+ - [物體檢測](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/11-ObjectDetection/README.md)
+ - [分割](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/12-Segmentation/README.md)
+ 
+## [自然語言處理](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/README.md)
+ - 在 Microsoft Learn 上
+    - [人工智能基礎：探索自然語言處理](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-cacaste)
+    - [使用 PyTorch 的自然語言處理](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste)
+    - [使用 TensorFlow 的自然語言處理](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste)
+ - [文本表示](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/README.md)
+    - 詞袋模型
+    - TF/IDF
+ - [語義嵌入](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/README.md)
+    - Word2Vec
+    - GloVE
+ - [語言建模](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling)
+ - [循環神經網絡](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/README.md)
+     - LSTM
+     - GRU
+ - [生成式循環網絡](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/README.md)
+ - [Transformer 和 BERT](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/README.md)
+ - [命名實體識別](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/19-NER/README.md)
+ - [文本生成和 GPT](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/20-LanguageModels/README.md)
+
+## 其他技術
+ - [遺傳算法](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/6-Other/21-GeneticAlgorithms/README.md)
+ - [深度強化學習](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/6-Other/22-DeepRL/README.md)
+ - [多代理系統](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/6-Other/23-MultiagentSystems/README.md)
+
+## [人工智能倫理](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/7-Ethics/README.md)
+ - [Microsoft Learn 負責任的人工智能](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste)
+
+## 附加內容
+ - [多模態網絡](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/X-Extras/X1-MultiModal/README.md)
+   - [CLIP](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/X-Extras/X1-MultiModal/Clip.ipynb)
+   - DALL-E
+   - VQ-GAN
+
+**免責聲明**：  
+本文件已使用人工智能翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。儘管我們致力於提供準確的翻譯，請注意自動翻譯可能包含錯誤或不準確之處。原始語言的文件應被視為權威來源。對於重要信息，建議使用專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或錯誤解釋不承擔責任。

translations/zh-HK/etc/SUPPORT.md

@@ -0,0 +1,14 @@
+# 支援
+
+## 如何提交問題及獲取協助  
+
+此項目使用 GitHub Issues 來追蹤錯誤及功能需求。在提交新問題之前，請先搜尋現有問題以避免重複。若需提交新問題，請將您的錯誤或功能需求作為新 Issue 提交。
+
+如需使用此項目時的協助或有任何疑問，請使用討論板。
+
+## Microsoft 支援政策  
+
+此項目的支援僅限於上述列出的資源。
+
+**免責聲明**：  
+本文件已使用人工智能翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。應以原文文件作為權威來源。如涉及關鍵資訊，建議尋求專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或錯誤解釋概不負責。

translations/zh-HK/etc/TRANSLATIONS.md

@@ -0,0 +1,36 @@
+# 參與翻譯課程
+
+我們歡迎您為這個課程的課程內容進行翻譯！
+
+## 指引
+
+每個課程資料夾和課程介紹資料夾中都有包含翻譯後的 Markdown 文件的資料夾。
+
+> 注意，請不要翻譯任何程式碼範例文件中的程式碼；唯一需要翻譯的是 README、作業和測驗。謝謝！
+
+翻譯後的文件應遵循以下命名規則：
+
+**README._[language]_.md**
+
+其中 _[language]_ 是根據 ISO 639-1 標準的兩位字母語言縮寫（例如，西班牙文為 `README.es.md`，荷蘭文為 `README.nl.md`）。
+
+**assignment._[language]_.md**
+
+與 README 類似，請翻譯作業文件。
+
+**測驗**
+
+1. 將您的翻譯新增到測驗應用程式中，方法是將文件新增到這裡：https://github.com/microsoft/AI-For-Beginners/tree/main/etc/quiz-app/src/assets/translations，並遵循正確的命名規則（例如 en.json、fr.json）。**請不要翻譯 'true' 或 'false' 這些詞語。謝謝！**
+
+2. 在測驗應用程式的 App.vue 文件中新增您的語言代碼到下拉選單中。
+
+3. 編輯測驗應用程式的 [translations index.js 文件](https://github.com/microsoft/AI-For-Beginners/blob/main/etc/quiz-app/src/assets/translations/index.js)，以新增您的語言。
+
+4. 最後，編輯您翻譯後的 README.md 文件中的所有測驗連結，讓它們直接指向您的翻譯測驗，例如：https://red-field-0a6ddfd03.1.azurestaticapps.net/quiz/1 改為 https://red-field-0a6ddfd03.1.azurestaticapps.net/quiz/1?loc=id
+
+**感謝您**
+
+我們由衷感謝您的努力！
+
+**免責聲明**：  
+本文件使用人工智能翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。應以原文文件作為權威來源。對於關鍵資訊，建議尋求專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或誤釋不承擔責任。

translations/zh-HK/etc/quiz-app/README.md

@@ -0,0 +1,128 @@
+# 測驗
+
+這些測驗是 AI 課程（https://aka.ms/ai-beginners）的課前和課後測驗。
+
+## 新增翻譯測驗集
+
+透過在 `assets/translations` 資料夾中建立相應的測驗結構來新增測驗翻譯。原始測驗位於 `assets/translations/en`。測驗依據課程分為多個組別。請確保編號與正確的測驗部分對齊。整個課程共有 40 個測驗，編號從 0 開始。
+
+編輯翻譯後，請編輯翻譯資料夾中的 `index.js` 檔案，按照 `en` 的慣例匯入所有檔案。
+
+接著，編輯 `assets/translations` 中的 `index.js` 檔案，匯入新的翻譯檔案。
+
+然後，編輯此應用程式中的 `App.vue` 下拉選單，新增您的語言。將本地化縮寫與您的語言資料夾名稱匹配。
+
+最後，編輯翻譯課程中的所有測驗連結（如果存在），以包含此本地化作為查詢參數，例如：`?loc=fr`。
+
+## 專案設定
+
+```
+npm install
+```
+
+### 編譯並熱重載以進行開發
+
+```
+npm run serve
+```
+
+### 編譯並壓縮以進行生產環境
+
+```
+npm run build
+```
+
+### 檢查並修復檔案
+
+```
+npm run lint
+```
+
+### 自訂配置
+
+請參閱 [配置參考](https://cli.vuejs.org/config/)。
+
+致謝：感謝此測驗應用程式的原始版本：https://github.com/arpan45/simple-quiz-vue
+
+## 部署到 Azure
+
+以下是幫助您開始的逐步指南：
+
+1. Fork GitHub 儲存庫  
+確保您的靜態網站應用程式程式碼位於您的 GitHub 儲存庫中。Fork 此儲存庫。
+
+2. 建立 Azure 靜態網站應用程式  
+- 建立 [Azure 帳戶](http://azure.microsoft.com)  
+- 前往 [Azure 入口網站](https://portal.azure.com)  
+- 點擊「建立資源」，然後搜尋「靜態網站應用程式」。  
+- 點擊「建立」。  
+
+3. 配置靜態網站應用程式  
+- 基本設定：  
+  - 訂閱：選擇您的 Azure 訂閱。  
+  - 資源群組：建立新的資源群組或使用現有的資源群組。  
+  - 名稱：為您的靜態網站應用程式提供一個名稱。  
+  - 區域：選擇最接近您使用者的區域。  
+
+- #### 部署詳細資訊：  
+  - 原始碼：選擇「GitHub」。  
+  - GitHub 帳戶：授權 Azure 存取您的 GitHub 帳戶。  
+  - 組織：選擇您的 GitHub 組織。  
+  - 儲存庫：選擇包含靜態網站應用程式的儲存庫。  
+  - 分支：選擇您要部署的分支。  
+
+- #### 建置詳細資訊：  
+  - 建置預設值：選擇您的應用程式所使用的框架（例如 React、Angular、Vue 等）。  
+  - 應用程式位置：指定包含應用程式程式碼的資料夾（例如，如果在根目錄，則為 /）。  
+  - API 位置：如果有 API，請指定其位置（可選）。  
+  - 輸出位置：指定生成輸出的資料夾（例如 build 或 dist）。  
+
+4. 檢查並建立  
+檢查您的設定，然後點擊「建立」。Azure 將設置必要的資源，並在您的儲存庫中建立 GitHub Actions 工作流程。
+
+5. GitHub Actions 工作流程  
+Azure 會自動在您的儲存庫中建立一個 GitHub Actions 工作流程檔案（.github/workflows/azure-static-web-apps-<name>.yml）。此工作流程將處理建置和部署過程。
+
+6. 監控部署  
+前往您的 GitHub 儲存庫中的「Actions」標籤。  
+您應該會看到一個正在運行的工作流程。此工作流程將建置並部署您的靜態網站應用程式到 Azure。  
+一旦工作流程完成，您的應用程式將在提供的 Azure URL 上線。
+
+### 範例工作流程檔案
+
+以下是 GitHub Actions 工作流程檔案的範例：  
+name: Azure Static Web Apps CI/CD  
+```
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+    types: [opened, synchronize, reopened, closed]
+    branches:
+      - main
+
+jobs:
+  build_and_deploy_job:
+    runs-on: ubuntu-latest
+    name: Build and Deploy Job
+    steps:
+      - uses: actions/checkout@v2
+      - name: Build And Deploy
+        id: builddeploy
+        uses: Azure/static-web-apps-deploy@v1
+        with:
+          azure_static_web_apps_api_token: ${{ secrets.AZURE_STATIC_WEB_APPS_API_TOKEN }}
+          repo_token: ${{ secrets.GITHUB_TOKEN }}
+          action: "upload"
+          app_location: "etc/quiz-app # App source code path"
+          api_location: ""API source code path optional
+          output_location: "dist" #Built app content directory - optional
+```
+
+### 其他資源
+- [Azure 靜態網站應用程式文件](https://learn.microsoft.com/azure/static-web-apps/getting-started)  
+- [GitHub Actions 文件](https://docs.github.com/actions/use-cases-and-examples/deploying/deploying-to-azure-static-web-app)  
+
+**免責聲明**：  
+本文件已使用人工智能翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。應以原文文件作為權威來源。對於關鍵資訊，建議尋求專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或錯誤解釋概不負責。

translations/zh-HK/examples/03-image-classifier.ipynb

@@ -0,0 +1,397 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 簡單圖像分類器\n",
+    "\n",
+    "此筆記本將教您如何使用預訓練的神經網絡進行圖像分類。\n",
+    "\n",
+    "**您將學到：**\n",
+    "- 如何載入並使用預訓練模型\n",
+    "- 圖像預處理\n",
+    "- 對圖像進行預測\n",
+    "- 理解信心分數\n",
+    "\n",
+    "**使用案例：** 識別圖像中的物體（例如「貓」、「狗」、「車」等）\n",
+    "\n",
+    "---\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 第一步：導入所需的庫\n",
+    "\n",
+    "讓我們導入所需的工具。不用擔心，如果你現在還不完全理解這些！\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Core libraries\n",
+    "import numpy as np\n",
+    "from PIL import Image\n",
+    "import requests\n",
+    "from io import BytesIO\n",
+    "\n",
+    "# TensorFlow for deep learning\n",
+    "try:\n",
+    "    import tensorflow as tf\n",
+    "    from tensorflow.keras.applications import MobileNetV2\n",
+    "    from tensorflow.keras.applications.mobilenet_v2 import preprocess_input, decode_predictions\n",
+    "    print(\"✅ TensorFlow loaded successfully!\")\n",
+    "    print(f\"   Version: {tf.__version__}\")\n",
+    "except ImportError:\n",
+    "    print(\"❌ Please install TensorFlow: pip install tensorflow\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 第 2 步：載入預訓練模型\n",
+    "\n",
+    "我們將使用 **MobileNetV2**，這是一個已經在數百萬張圖片上訓練過的神經網絡。\n",
+    "\n",
+    "這被稱為 **遷移學習**——使用別人訓練好的模型！\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(\"📦 Loading pre-trained MobileNetV2 model...\")\n",
+    "print(\"   This may take a minute on first run (downloading weights)...\")\n",
+    "\n",
+    "# Load the model\n",
+    "# include_top=True means we use the classification layer\n",
+    "# weights='imagenet' means it was trained on ImageNet dataset\n",
+    "model = MobileNetV2(weights='imagenet', include_top=True)\n",
+    "\n",
+    "print(\"✅ Model loaded!\")\n",
+    "print(f\"   The model can recognize 1000 different object categories\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 第三步：輔助函數\n",
+    "\n",
+    "讓我們建立一些函數來載入並準備圖片，以供模型使用。\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def load_image_from_url(url):\n",
+    "    \"\"\"\n",
+    "    Load an image from a URL.\n",
+    "    \n",
+    "    Args:\n",
+    "        url: Web address of the image\n",
+    "        \n",
+    "    Returns:\n",
+    "        PIL Image object\n",
+    "    \"\"\"\n",
+    "    response = requests.get(url)\n",
+    "    img = Image.open(BytesIO(response.content))\n",
+    "    return img\n",
+    "\n",
+    "\n",
+    "def prepare_image(img):\n",
+    "    \"\"\"\n",
+    "    Prepare an image for the model.\n",
+    "    \n",
+    "    Steps:\n",
+    "    1. Resize to 224x224 (model's expected size)\n",
+    "    2. Convert to array\n",
+    "    3. Add batch dimension\n",
+    "    4. Preprocess for MobileNetV2\n",
+    "    \n",
+    "    Args:\n",
+    "        img: PIL Image\n",
+    "        \n",
+    "    Returns:\n",
+    "        Preprocessed image array\n",
+    "    \"\"\"\n",
+    "    # Resize to 224x224 pixels\n",
+    "    img = img.resize((224, 224))\n",
+    "    \n",
+    "    # Convert to numpy array\n",
+    "    img_array = np.array(img)\n",
+    "    \n",
+    "    # Add batch dimension (model expects multiple images)\n",
+    "    img_array = np.expand_dims(img_array, axis=0)\n",
+    "    \n",
+    "    # Preprocess for MobileNetV2\n",
+    "    img_array = preprocess_input(img_array)\n",
+    "    \n",
+    "    return img_array\n",
+    "\n",
+    "\n",
+    "def classify_image(img):\n",
+    "    \"\"\"\n",
+    "    Classify an image and return top predictions.\n",
+    "    \n",
+    "    Args:\n",
+    "        img: PIL Image\n",
+    "        \n",
+    "    Returns:\n",
+    "        List of (class_name, confidence) tuples\n",
+    "    \"\"\"\n",
+    "    # Prepare the image\n",
+    "    img_array = prepare_image(img)\n",
+    "    \n",
+    "    # Make prediction\n",
+    "    predictions = model.predict(img_array, verbose=0)\n",
+    "    \n",
+    "    # Decode predictions to human-readable labels\n",
+    "    # top=5 means we get the top 5 most likely classes\n",
+    "    decoded = decode_predictions(predictions, top=5)[0]\n",
+    "    \n",
+    "    # Convert to simpler format\n",
+    "    results = [(label, float(confidence)) for (_, label, confidence) in decoded]\n",
+    "    \n",
+    "    return results\n",
+    "\n",
+    "\n",
+    "print(\"✅ Helper functions ready!\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 第四步：使用範例圖片進行測試\n",
+    "\n",
+    "讓我們嘗試分類一些來自互聯網的圖片吧！\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Sample images to classify\n",
+    "# These are from Unsplash (free stock photos)\n",
+    "test_images = [\n",
+    "    {\n",
+    "        \"url\": \"https://images.unsplash.com/photo-1514888286974-6c03e2ca1dba?w=400\",\n",
+    "        \"description\": \"A cat\"\n",
+    "    },\n",
+    "    {\n",
+    "        \"url\": \"https://images.unsplash.com/photo-1552053831-71594a27632d?w=400\",\n",
+    "        \"description\": \"A dog\"\n",
+    "    },\n",
+    "    {\n",
+    "        \"url\": \"https://images.unsplash.com/photo-1511919884226-fd3cad34687c?w=400\",\n",
+    "        \"description\": \"A car\"\n",
+    "    },\n",
+    "]\n",
+    "\n",
+    "print(f\"🧪 Testing on {len(test_images)} images...\")\n",
+    "print(\"=\" * 70)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 分類每張圖片\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for i, img_data in enumerate(test_images, 1):\n",
+    "    print(f\"\\n📸 Image {i}: {img_data['description']}\")\n",
+    "    print(\"-\" * 70)\n",
+    "    \n",
+    "    try:\n",
+    "        # Load image\n",
+    "        img = load_image_from_url(img_data['url'])\n",
+    "        \n",
+    "        # Display image\n",
+    "        display(img.resize((200, 200)))  # Show smaller version\n",
+    "        \n",
+    "        # Classify\n",
+    "        results = classify_image(img)\n",
+    "        \n",
+    "        # Show predictions\n",
+    "        print(\"\\n🎯 Top 5 Predictions:\")\n",
+    "        for rank, (label, confidence) in enumerate(results, 1):\n",
+    "            # Create a visual bar\n",
+    "            bar_length = int(confidence * 50)\n",
+    "            bar = \"█\" * bar_length\n",
+    "            \n",
+    "            print(f\"  {rank}. {label:20s} {confidence*100:5.2f}% {bar}\")\n",
+    "        \n",
+    "    except Exception as e:\n",
+    "        print(f\"❌ Error: {e}\")\n",
+    "\n",
+    "print(\"\\n\" + \"=\" * 70)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 第五步：嘗試使用自己的圖片！\n",
+    "\n",
+    "將下面的 URL 替換為您想要分類的任何圖片 URL。\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Try your own image!\n",
+    "# Replace this URL with any image URL\n",
+    "custom_image_url = \"https://images.unsplash.com/photo-1472491235688-bdc81a63246e?w=400\"  # A flower\n",
+    "\n",
+    "print(\"🖼️  Classifying your custom image...\")\n",
+    "print(\"=\" * 70)\n",
+    "\n",
+    "try:\n",
+    "    # Load and show image\n",
+    "    img = load_image_from_url(custom_image_url)\n",
+    "    display(img.resize((300, 300)))\n",
+    "    \n",
+    "    # Classify\n",
+    "    results = classify_image(img)\n",
+    "    \n",
+    "    # Show results\n",
+    "    print(\"\\n🎯 Top 5 Predictions:\")\n",
+    "    print(\"-\" * 70)\n",
+    "    for rank, (label, confidence) in enumerate(results, 1):\n",
+    "        bar_length = int(confidence * 50)\n",
+    "        bar = \"█\" * bar_length\n",
+    "        print(f\"  {rank}. {label:20s} {confidence*100:5.2f}% {bar}\")\n",
+    "    \n",
+    "    # Highlight top prediction\n",
+    "    top_label, top_confidence = results[0]\n",
+    "    print(\"\\n\" + \"=\" * 70)\n",
+    "    print(f\"\\n🏆 Best guess: {top_label} ({top_confidence*100:.2f}% confident)\")\n",
+    "    \n",
+    "except Exception as e:\n",
+    "    print(f\"❌ Error: {e}\")\n",
+    "    print(\"   Make sure the URL points to a valid image!\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 💡 剛剛發生了什麼？\n",
+    "\n",
+    "1. **我們載入了一個預訓練模型** - MobileNetV2 已經在數百萬張圖片上進行過訓練  \n",
+    "2. **我們預處理了圖片** - 將圖片調整大小並格式化以適配模型  \n",
+    "3. **模型進行了預測** - 輸出了對1000個物件類別的概率  \n",
+    "4. **我們解碼了結果** - 將數字轉換為人類可讀的標籤  \n",
+    "\n",
+    "### 理解信心分數\n",
+    "\n",
+    "- **90-100%**：非常有信心（幾乎肯定正確）  \n",
+    "- **70-90%**：有信心（可能正確）  \n",
+    "- **50-70%**：有些信心（可能正確）  \n",
+    "- **低於50%**：信心不足（不確定）  \n",
+    "\n",
+    "### 為什麼預測可能會出錯？\n",
+    "\n",
+    "- **不尋常的角度或光線** - 模型是在典型照片上訓練的  \n",
+    "- **多個物件** - 模型預期只有一個主要物件  \n",
+    "- **罕見物件** - 模型只認識1000個類別  \n",
+    "- **低質量圖片** - 模糊或像素化的圖片更難辨識  \n",
+    "\n",
+    "---\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 🚀 下一步\n",
+    "\n",
+    "1. **嘗試不同的圖片：**\n",
+    "   - 在 [Unsplash](https://unsplash.com) 上尋找圖片\n",
+    "   - 右鍵點擊 → 「複製圖片地址」以獲取 URL\n",
+    "\n",
+    "2. **進行實驗：**\n",
+    "   - 抽象藝術會有什麼效果？\n",
+    "   - 它能否識別不同角度的物體？\n",
+    "   - 它如何處理多個物體？\n",
+    "\n",
+    "3. **深入學習：**\n",
+    "   - 探索 [電腦視覺課程](../lessons/4-ComputerVision/README.md)\n",
+    "   - 學習如何訓練自己的圖片分類器\n",
+    "   - 理解 CNN（卷積神經網絡）的工作原理\n",
+    "\n",
+    "---\n",
+    "\n",
+    "## 🎉 恭喜！\n",
+    "\n",
+    "你剛剛使用最先進的神經網絡構建了一個圖片分類器！\n",
+    "\n",
+    "這種技術同樣應用於：\n",
+    "- Google Photos（整理你的照片）\n",
+    "- 自動駕駛汽車（識別物體）\n",
+    "- 醫學診斷（分析 X 光片）\n",
+    "- 品質控制（檢測缺陷）\n",
+    "\n",
+    "繼續探索和學習吧！🚀\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n---\n\n**免責聲明**：  \n本文件已使用人工智能翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。儘管我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。原始文件的母語版本應被視為權威來源。對於重要信息，建議使用專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或錯誤解釋概不負責。\n"
+   ]
+  }
+ ],
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+    "version": 3
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+   "mimetype": "text/x-python",
+   "name": "python",
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+   "language_code": "hk"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

translations/zh-HK/examples/README.md

@@ -0,0 +1,85 @@
+# 初學者友善的 AI 範例
+
+歡迎！此目錄包含簡單、獨立的範例，幫助你開始學習 AI 和機器學習。每個範例都設計得易於理解，並附有詳細的註解和逐步解說。
+
+## 📚 範例概覽
+
+| 範例 | 描述 | 難度 | 先決條件 |
+|------|------|------|----------|
+| [Hello AI World](../../../examples/01-hello-ai-world.py) | 你的第一個 AI 程式 - 簡單的模式識別 | ⭐ 初學者 | Python 基礎 |
+| [Simple Neural Network](../../../examples/02-simple-neural-network.py) | 從零開始建立一個神經網絡 | ⭐⭐ 初學者+ | Python、基礎數學 |
+| [Image Classifier](./03-image-classifier.ipynb) | 使用預訓練模型進行圖片分類 | ⭐⭐ 初學者+ | Python、numpy |
+| [Text Sentiment](../../../examples/04-text-sentiment.py) | 分析文字情感（正面/負面） | ⭐⭐ 初學者+ | Python |
+
+## 🚀 開始使用
+
+### 先決條件
+
+請確保已安裝 Python（建議使用 3.8 或更高版本）。安裝所需的套件：
+
+```bash
+# For Python scripts
+pip install numpy
+
+# For Jupyter notebooks (image classifier)
+pip install jupyter numpy pillow tensorflow
+```
+
+或者使用主課程中的 conda 環境：
+
+```bash
+conda env create --name ai4beg --file ../environment.yml
+conda activate ai4beg
+```
+
+### 執行範例
+
+**對於 Python 腳本 (.py 檔案):**
+```bash
+python 01-hello-ai-world.py
+```
+
+**對於 Jupyter 筆記本 (.ipynb 檔案):**
+```bash
+jupyter notebook 03-image-classifier.ipynb
+```
+
+## 📖 學習路徑
+
+我們建議按照以下順序學習範例：
+
+1. **從 "Hello AI World" 開始** - 學習模式識別的基礎
+2. **建立一個簡單的神經網絡** - 理解神經網絡的運作方式
+3. **嘗試圖片分類器** - 使用真實圖片體驗 AI 的應用
+4. **分析文字情感** - 探索自然語言處理
+
+## 💡 初學者提示
+
+- **仔細閱讀程式碼註解** - 它們解釋了每一行的作用
+- **多嘗試！** - 嘗試更改數值並觀察結果
+- **不用擔心完全理解** - 學習是需要時間的
+- **提出問題** - 使用 [討論板](https://github.com/microsoft/AI-For-Beginners/discussions)
+
+## 🔗 下一步
+
+完成這些範例後，探索完整課程：
+- [AI 簡介](../lessons/1-Intro/README.md)
+- [神經網絡](../lessons/3-NeuralNetworks/README.md)
+- [電腦視覺](../lessons/4-ComputerVision/README.md)
+- [自然語言處理](../lessons/5-NLP/README.md)
+
+## 🤝 貢獻
+
+覺得這些範例有幫助嗎？幫助我們改進：
+- 回報問題或提出改進建議
+- 添加更多適合初學者的範例
+- 改善文件和註解
+
+---
+
+*記住：每位專家都曾是初學者。祝學習愉快！ 🎓*
+
+---
+
+**免責聲明**：  
+本文件已使用 AI 翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。雖然我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。原始文件的母語版本應被視為權威來源。對於重要資訊，建議使用專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或錯誤解釋概不負責。