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  **專為 NotebookLM 生成的 PDF 講義設計的逆向工程工具** **一鍵上傳,自動分離「純文字內容」與「乾淨背景圖」,讓你的素材可以二次利用!** <h3>🧠 補腦專區:<a href="https://deep-learning-101.github.io/" target="_blank">Deep Learning 101</a></h3>
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- | 🔥 技術傳送門 (Tech Stack) | 📚 必讀心法 (Must Read) |
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- | :--- | :--- |
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- | 🤖 [**大語言模型 (LLM)**](https://deep-learning-101.github.io/Large-Language-Model) | 🏹 [**策略篇:企業入門策略**](https://deep-learning-101.github.io/Blog/AIBeginner) |
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- | 📝 [**自然語言處理 (NLP)**](https://deep-learning-101.github.io/Natural-Language-Processing) | 📊 [**評測篇:臺灣 LLM 分析**](https://deep-learning-101.github.io/Blog/TW-LLM-Benchmark) |
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- | 👁️ [**電腦視覺 (CV)**](https://deep-learning-101.github.io//Computer-Vision) | 🛠️ [**實戰篇:打造高精準 RAG**](https://deep-learning-101.github.io/RAG) |
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- | 🎤 [**語音處理 (Speech)**](https://deep-learning-101.github.io/Speech-Processing) | 🕳️ [**避坑篇:AI Agent 開發陷阱**](https://deep-learning-101.github.io/agent) |
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  </div>
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  **專為 NotebookLM 生成的 PDF 講義設計的逆向工程工具** **一鍵上傳,自動分離「純文字內容」與「乾淨背景圖」,讓你的素材可以二次利用!** <h3>🧠 補腦專區:<a href="https://deep-learning-101.github.io/" target="_blank">Deep Learning 101</a></h3>
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+ | 🔥 技術傳送門 (Tech Stack) | 📚 必讀心法 (Must Read) |
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+ | :--- | :--- |
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+ | 🤖 [**大語言模型 (LLM)**](https://deep-learning-101.github.io/Large-Language-Model) | 🏹 [**策略篇:企業入門策略**](https://deep-learning-101.github.io/Blog/AIBeginner) |
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+ | 📝 [**自然語言處理 (NLP)**](https://deep-learning-101.github.io/Natural-Language-Processing) | 📊 [**評測篇:臺灣 LLM 分析**](https://deep-learning-101.github.io/Blog/TW-LLM-Benchmark) |
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+ | 👁️ [**電腦視覺 (CV)**](https://deep-learning-101.github.io//Computer-Vision) | 🛠️ [**實戰篇:打造高精準 RAG**](https://deep-learning-101.github.io/RAG) |
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+ | 🎤 [**語音處理 (Speech)**](https://deep-learning-101.github.io/Speech-Processing) | 🕳️ [**避坑篇:AI Agent 開發陷阱**](https://deep-learning-101.github.io/agent) |
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  </div>
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