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[](https://discord.gg/nTYy5BXMWG)
# 人工智能初學者課程
||
|:---:|
| AI For Beginners - _速寫筆記由 [@girlie_mac](https://twitter.com/girlie_mac) 製作_ |
跟隨我們為期12星期、包含24課堂的課程，一同探索人工智能(AI)的世界！課程包括實際應用課堂、測驗以及實驗室。此課程適合初學者，涵蓋工具如 TensorFlow 及 PyTorch，亦探討 AI 的倫理問題。
### 🌐 多語言支援
#### 透過 GitHub Action 支援（自動且時時更新）
[Arabic](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgarian](../bg/README.md) | [Burmese (Myanmar)](../my/README.md) | [Chinese (Simplified)](../zh-CN/README.md) | [Chinese (Traditional, Hong Kong)](./README.md) | [Chinese (Traditional, Macau)](../zh-MO/README.md) | [Chinese (Traditional, Taiwan)](../zh-TW/README.md) | [Croatian](../hr/README.md) | [Czech](../cs/README.md) | [Danish](../da/README.md) | [Dutch](../nl/README.md) | [Estonian](../et/README.md) | [Finnish](../fi/README.md) | [French](../fr/README.md) | [German](../de/README.md) | [Greek](../el/README.md) | [Hebrew](../he/README.md) | [Hindi](../hi/README.md) | [Hungarian](../hu/README.md) | [Indonesian](../id/README.md) | [Italian](../it/README.md) | [Japanese](../ja/README.md) | [Kannada](../kn/README.md) | [Khmer](../km/README.md) | [Korean](../ko/README.md) | [Lithuanian](../lt/README.md) | [Malay](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegian](../no/README.md) | [Persian (Farsi)](../fa/README.md) | [Polish](../pl/README.md) | [Portuguese (Brazil)](../pt-BR/README.md) | [Portuguese (Portugal)](../pt-PT/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romanian](../ro/README.md) | [Russian](../ru/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenian](../sl/README.md) | [Spanish](../es/README.md) | [Swahili](../sw/README.md) | [Swedish](../sv/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkish](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamese](../vi/README.md)
> **想要本地克隆？**
>
> 此倉庫包含超過50種語言翻譯，導致下載檔案較大。若想不下載翻譯資料，可以使用稀疏檢出：
>
> **Bash / macOS / Linux:**
> ```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'
> ```
>
> **CMD (Windows):**
> ```cmd
> 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"
> ```
>
> 這樣可以讓你快速下載，取得所有完成課程所需的資源。
**如果您希望支持更多翻譯語言，請參閱[這裡](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## 加入社群
[](https://discord.gg/nTYy5BXMWG)
## 你將學到什麼
**[課程心智圖](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，包括以知識表達與推理為核心的經典符號方法（[GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)）。
* 現代 AI 核心的神經網絡及深度學習。我們將透過代碼示範兩個最受歡迎框架 [TensorFlow](http://Tensorflow.org) 與 [PyTorch](http://pytorch.org) 的基本概念。
* 適用於圖片與文本的神經架構。會介紹近期模型，但可能未必涵蓋最新最前沿。
* 少數較不常用的 AI 方法，如遺傳算法與多智能體系統。
本課程不涵蓋：
> [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)
* 商業案例中的AI 應用。建議參考 Microsoft Learn 上的[AI 商務用戶入門](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum)課程路徑，或與[INSEAD](https://www.insead.edu/)合作開發的[AI 商業學校](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)。
* 經典機器學習，可參考我們的[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)構建的實際 AI 應用。建議先從 Microsoft Learn 上的 [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)、**[Azure OpenAI 服務生成式 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 等模組開始學習。
* 具體的機器學習雲端平台，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)。可參考 [使用 Azure Machine Learning 構建與運營機器學習解決方案](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) 與 [使用 Azure Databricks 構建與運營機器學習解決方案](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum)。
* 對話式 AI及聊天機械人。有專門的[聊天式 AI 解決方案](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum)課程路徑，亦可參考此[部落格文章](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)作詳盡了解。
* 深入的深度學習數學。推薦閱讀 Ian Goodfellow、Yoshua Bengio 與 Aaron Courville 合著的《[Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)》，線上版本在[https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)。
對於初探 *AI 雲端* 主題，可考慮 Microsoft Learn 的 [Azure 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
| | 課堂鏈接 | PyTorch/Keras/TensorFlow | 實驗室 |
| :-: | :-------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [設定課程環境](./lessons/0-course-setup/setup.md) | [開發環境設定指南](./lessons/0-course-setup/how-to-run.md) | |
| I | [人工智能簡介](./lessons/1-Intro/README.md) | | |
| 01 | [人工智能介紹與歷史](./lessons/1-Intro/README.md) | - | - |
| II | **符號 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) /[概念圖譜](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [神經網絡導論](./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](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [多層感知器與創建我們自己的框架](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [筆記本](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [實驗](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [框架入門（PyTorch/TensorFlow）及過擬合](./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](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [計算機視覺](./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 探索計算機視覺](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [計算機視覺入門。OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [筆記本](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [實驗](./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](./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) 和 [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](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [自編碼器與變分自編碼器](./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轉換](./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](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [語義分割。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 | [語義詞向量。Word2Vec 與 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。訓練你自己的詞向量](./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](./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 | [生成式循環網絡](./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](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformer。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](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [大型語言模型，提示程式設計與少量示例任務](./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](./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 | 額外內容 | | |
| 25 | [多模態網絡，CLIP 與 VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [筆記本](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## 每堂課包括
* 預讀資料
* 可執行的 Jupyter 筆記本，通常針對特定架構（**PyTorch** 或 **TensorFlow**）。可執行的筆記本還包含大量理論資料，因此了解主題需要至少通讀一個版本的筆記本（PyTorch 或 TensorFlow 其中一個）。
* 部分主題提供的 實驗，讓您有機會將所學的內容應用於具體問題。
* 有些章節包含指向涵蓋相關主題的 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 模組的連結。
## 開始使用
### 🎯 AI 新手？由此開始！
如果您是 AI 完全新手，想要快速入門和動手範例，請參閱我們的 [新手友好範例](./examples/README.md)！這些範例包括：
- 🌟 **Hello AI World** — 您的第一個 AI 程式（模式識別）
- 🧠 簡單神經網絡 — 從零開始建立神經網絡
- 🖼️ 圖像分類器 — 搭配詳細註解的圖像分類
- 💬 文本情感分析 — 分析正面/負面文本
這些範例旨在幫助您在深入完整課程前了解 AI 概念。
### 📚 完整課程設置
- 我們已建立了一個[設置課程](./lessons/0-course-setup/setup.md)，幫助您建立開發環境。 - 教師專用，我們也有建立[課程設置課程](./lessons/0-course-setup/for-teachers.md)！
- 如何[在 VSCode 或 Codespace 中運行程式碼](./lessons/0-course-setup/how-to-run.md)
請依照以下步驟：
Fork 倉庫：點擊本頁右上角的「Fork」按鈕。
Clone 倉庫：`git clone https://github.com/microsoft/AI-For-Beginners.git`
別忘了給這個倉庫星標 (🌟)，方便日後查找。
## 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)，與其他參與本課程的學習者交流並獲得支援。
若在開發過程中有產品反饋或疑問，請訪問我們的[Azure AI Foundry 開發者論壇](https://aka.ms/foundry/forum)
## 小測驗
> 關於小測驗的說明：所有小測驗均收錄於 etc\quiz-app 中的 Quiz-app 資料夾，或可[線上訪問](https://ff-quizzes.netlify.app/)。這些小測驗與課程內容相關聯，Quiz-app 可在本地運行或部署至 Azure；請遵循 `quiz-app` 資料夾中的說明。小測驗正在逐步本地化中。
## 需要協助
您有建議或發現拼寫或程式錯誤嗎？請提出 Issue 或發起 Pull Request。
## 特別感謝
* **✍️ 主要作者：** [Dmitry Soshnikov](http://soshnikov.com)，博士
* **🔥 編輯：** [Jen Looper](https://twitter.com/jenlooper)，博士
* **🎨 手繪筆記插畫師：** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ 小測驗創建者：** [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
我們團隊提供其他課程！請參考：
### LangChain
[](https://aka.ms/langchain4j-for-beginners)
[](https://aka.ms/langchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin)
[](https://github.com/microsoft/langchain-for-beginners?WT.mc_id=m365-94501-dwahlin)
---
### Azure / Edge / MCP / Agents
[](https://github.com/microsoft/AZD-for-beginners?WT.mc_id=academic-105485-koreyst)
[](https://github.com/microsoft/edgeai-for-beginners?WT.mc_id=academic-105485-koreyst)
[](https://github.com/microsoft/mcp-for-beginners?WT.mc_id=academic-105485-koreyst)
[](https://github.com/microsoft/ai-agents-for-beginners?WT.mc_id=academic-105485-koreyst)
---
### 生成式 AI 系列
[](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst)
[-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst)
[-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst)
[-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
[](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst)
[](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst)
[](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst)
[](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung)
[](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst)
[](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst)
[](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst)
---
### Copilot 系列
[](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst)
[](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst)
[](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst)
## 尋求協助
如果您遇到困難或有任何關於開發 AI 應用的問題，請加入與 MCP 相關的學習者與資深開發者討論。這是一個充滿支持的社群，歡迎提問並自由分享知識。
[](https://discord.gg/nTYy5BXMWG)
如果在開發時有產品反饋或錯誤，請訪問：
[](https://aka.ms/foundry/forum)
---
**免責聲明**：
本文件是使用 AI 翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 翻譯而成。雖然我們致力於確保準確性，但請注意自動翻譯可能會包含錯誤或不準確之處。原始文件的母語版本應視為權威來源。對於重要資訊，建議使用專業人工翻譯。我們不對因使用此翻譯而產生的任何誤解或誤釋負責。