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<p>涵盖Python语法、数据结构、函数和面向对象编程的基础练习，适合初学者快速上手。</p>
<a class="colab-badge" href="https://colab.research.google.com/drive/example-python-basics" target="_blank">
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<h4>NumPy矩阵运算</h4>
<p>NumPy数组操作、矩阵乘法、广播机制、线性代数运算等核心概念的实践练习。</p>
<a class="colab-badge" href="https://colab.research.google.com/drive/example-numpy-operations" target="_blank">
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<div class="colab-icon">📉</div>
<h4>梯度下降可视化</h4>
<p>交互式可视化梯度下降算法，理解学习率、收敛过程和不同优化器的行为差异。</p>
<a class="colab-badge" href="https://colab.research.google.com/drive/example-gradient-descent" target="_blank">
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<div class="colab-card">
<div class="colab-icon">🎯</div>
<h4>K-Means聚类</h4>
<p>实现K-Means算法，理解聚类原理、肘部法则和不同初始化策略对结果的影响。</p>
<a class="colab-badge" href="https://colab.research.google.com/drive/example-kmeans-clustering" target="_blank">
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<div class="colab-icon">🖼️</div>
<h4>PyTorch CNN</h4>
<p>使用PyTorch构建卷积神经网络，在CIFAR-10数据集上进行图像分类训练。</p>
<a class="colab-badge" href="https://colab.research.google.com/drive/example-pytorch-cnn" target="_blank">
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<h4>Transformer Self-Attention</h4>
<p>从零实现Self-Attention机制，可视化注意力权重，理解Transformer的核心原理。</p>
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<h4>LLM文本生成</h4>
<p>使用Hugging Face Transformers加载预训练模型，进行文本生成和提示工程实验。</p>
<a class="colab-badge" href="https://colab.research.google.com/drive/example-llm-text-generation" target="_blank">
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<h4>LangChain RAG</h4>
<p>构建完整的RAG应用，包括文档加载、向量存储、检索和问答链的实现。</p>
<a class="colab-badge" href="https://colab.research.google.com/drive/example-langchain-rag" target="_blank">
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<h4>LangChain Agent</h4>
<p>创建能使用工具的AI Agent，实现ReAct推理循环，让模型自主完成复杂任务。</p>
<a class="colab-badge" href="https://colab.research.google.com/drive/example-langchain-agent" target="_blank">
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<h4>个人AI助手项目</h4>
<p>综合运用所学知识，构建一个具备记忆、工具使用和知识库的个人AI助手。</p>
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<h3><i class="fas fa-graduation-cap"></i> AI学习笔记</h3>
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<p>涵盖前置基础、核心原理、工程实践、应用工具、进阶展望</p>
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<h3><i class="fas fa-bookmark"></i> 内容导航</h3>
<p>第1-11章：基础与核心（见 ai-notes-core.html）</p>
<p>第12-23章：工程实践与进阶（本文件）</p>
<p>附录A：GPU与算力指南</p>
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