目录

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                  环境说明
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            <p aria-level="2" class="caption" role="heading">
              <span class="caption-text"> 监督学习：回归 </span>
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                <a class="reference internal" href="chapter01-01-lab-machine-learning-overview-and-examples.html">
                  1. 机器学习综述及示例
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                <a class="reference internal" href="chapter01-02-lab-linear-regression-implementation-and-applications.html">
                  2. 线性回归实现与应用
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                  3. 北京市住房价格预测
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                <a class="reference internal" href="chapter01-04-lab-polynomial-regression-implementation-and-applications.html">
                  4. 多项式回归实现与应用
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                <a class="reference internal" href="chapter01-05-challenge-bitcoin-price-prediction-and-visualization.html">
                  5. 比特币价格预测及绘图
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                <a class="reference internal" href="chapter01-06-lab-implementation-of-ridge-regression-and-lasso-regression.html">
                  6. 岭回归和 LASSO 回归实现
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                <a class="reference internal" href="chapter01-07-challenge-computing-ridge-regression-coefficients-with-matrix-operations.html">
                  7. 使用矩阵计算岭回归系数
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                <a class="reference internal" href="chapter01-08-lab-evaluation-and-validation-of-regression-models.html">
                  8. 回归模型评价与检验
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                <a class="reference internal" href="chapter01-09-challenge-comprehensive-practical-application-of-regression-methods.html">
                  9. 回归方法综合应用练习
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            <p aria-level="2" class="caption" role="heading">
              <span class="caption-text"> 监督学习：分类 </span>
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                <a class="reference internal" href="chapter02-01-lab-logistic-regression-implementation-and-applications.html">
                  10. 逻辑回归实现与应用
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                <a class="reference internal" href="chapter02-02-challenge-gradient-descent-method-implementation-and-applications.html">
                  11. 梯度下降法实现与应用
                </a>
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                <a class="reference internal" href="chapter02-03-lab-implementation-and-applications-of-the-k-nearest-neighbors-algorithm.html">
                  12. K 近邻算法实现与应用
                </a>
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                <a class="reference internal" href="chapter02-04-challenge-implementation-and-application-of-k-nearest-neighbors-regression-algorithm.html">
                  13. K 近邻回归算法实现与应用
                </a>
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                <a class="reference internal" href="chapter02-05-lab-naive-bayes-implementation-and-applications.html">
                  14. 朴素贝叶斯实现及应用
                </a>
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                <a class="reference internal" href="chapter02-06-challenge-implementation-and-visualization-of-the-gaussian-distribution-function.html">
                  15. 高斯分布函数实现及绘图
                </a>
              </li>
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                <a class="reference internal" href="chapter02-07-lab-evaluation-methods-for-classification-models.html">
                  16. 分类模型评价方法
                </a>
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                <a class="reference internal" href="chapter02-08-lab-support-vector-machines-implementation-and-applications.html">
                  17. 支持向量机实现与应用
                </a>
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                <a class="reference internal" href="chapter02-09-challenge-support-vector-machine-for-human-portrait-classification.html">
                  18. 支持向量机实现人像分类
                </a>
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                <a class="reference internal" href="chapter02-10-lab-decision-tree-implementation-and-applications.html">
                  19. 决策树实现与应用
                </a>
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                <a class="reference internal" href="chapter02-11-challenge-optimization-and-selection-of-decision-tree-model-parameters.html">
                  20. 决策树模型参数优化及选择
                </a>
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                <a class="reference internal" href="chapter02-12-lab-integrated-learning-method-for-bagging-and-boosting.html">
                  21. 装袋和提升集成学习方法
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                <a class="reference internal" href="chapter02-13-challenge-application-of-heterogeneous-ensemble-voting-methods.html">
                  22. 异质集成投票方法应用
                </a>
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                <a class="reference internal" href="chapter02-14-challenge-model-selection-with-cross-validation.html">
                  23. 使用交叉验证快速选择模型
                </a>
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            </ul>
            <p aria-level="2" class="caption" role="heading">
              <span class="caption-text"> 无监督学习：聚类 </span>
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                <a class="reference internal" href="chapter03-01-lab-clustering-methods-implementation-and-applications.html">
                  24. 划分聚类方法实现与应用
                </a>
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                <a class="reference internal" href="chapter03-02-challenge-image-compression-using-k-means-clustering.html">
                  25. 使用 K-Means 完成图像压缩
                </a>
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                <a class="reference internal" href="chapter03-03-lab-implementation-and-applications-of-hierarchical-clustering-methods.html">
                  26. 层次聚类方法实现与应用
                </a>
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                <a class="reference internal" href="chapter03-04-lab-principle-and-applications-of-principal-component-analysis.html">
                  27. 主成分分析原理及应用
                </a>
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                <a class="reference internal" href="chapter03-05-challenge-hierarchical-clustering-applications-and-dendrogram-visualization.html">
                  28. 层次聚类应用及聚类树绘制
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                <a class="reference internal" href="chapter03-06-lab-implementation-and-applications-of-density-based-clustering-algorithms.html">
                  29. 密度聚类方法实现与应用
                </a>
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                <a class="reference internal" href="chapter03-07-challenge-density-based-clustering-for-anomaly-detection-in-shared-bike-systems.html">
                  30. 密度聚类标记异常共享单车
                </a>
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                <a class="reference internal" href="chapter03-08-lab-application-of-spectral-clustering-and-other-clustering-methods.html">
                  31. 谱聚类及其他聚类方法应用
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                <a class="reference internal" href="chapter03-09-challenge-comparative-evaluation-of-common-clustering-algorithms.html">
                  32. 常用聚类算法对比评估
                </a>
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            </ul>
            <p aria-level="2" class="caption" role="heading">
              <span class="caption-text"> 无监督学习：关联规则 </span>
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                <a class="reference internal" href="chapter04-01-lab-apriori-association-rule-learning-algorithm.html">
                  33. Apriori 关联规则学习方法
                </a>
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                <a class="reference internal" href="chapter04-02-challenge-analysis-of-association-rules-in-shopping-data.html">
                  34. 购物数据关联规则分析
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                <a class="reference internal" href="chapter04-03-lab-time-series-data-analysis-and-processing.html">
                  35. 时间序列数据分析处理
                </a>
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                <a class="reference internal" href="chapter04-04-challenge-stock-time-series-data-processing.html">
                  36. 股票时间序列数据处理
                </a>
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                <a class="reference internal" href="chapter04-05-lab-modelling-and-analysis-of-time-series-data.html">
                  37. 时间序列数据建模分析
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                <a class="reference internal" href="chapter04-06-challenge-modeling-and-analysis-of-agricultural-production-index.html">
                  38. 农业生产指数建模分析
                </a>
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            </ul>
            <p aria-level="2" class="caption" role="heading">
              <span class="caption-text"> 机器学习工程：模型部署和推理 </span>
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                <a class="reference internal" href="chapter05-01-lab-a-comprehensive-review-of-automated-machine-learning.html">
                  39. 自动化机器学习综述
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                <a class="reference internal" href="chapter05-02-lab-automated-machine-learning-practices-and-applications.html">
                  40. 自动化机器学习实践应用
                </a>
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                <a class="reference internal" href="chapter05-03-challenge-automl-for-handwritten-character-classification.html">
                  41. AutoML 完成手写字符分类
                </a>
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                <a class="reference internal" href="chapter05-04-lab-machine-learning-model-inference-and-deployment.html">
                  42. 机器学习模型推理与部署
                </a>
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                <a class="reference internal" href="chapter05-05-challenge-mushroom-classification-model-deployment-and-inference.html">
                  43. 蘑菇分类模型部署和推理
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                <a class="reference internal" href="chapter05-06-lab-dynamic-incremental-training-of-machine-learning-models.html">
                  44. 机器学习模型动态增量训练
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                <a class="reference internal" href="chapter05-07-challenge-online-learning-and-cloud-model-deployment.html">
                  45. 在线学习及云端模型部署
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            </ul>
            <p aria-level="2" class="caption" role="heading">
              <span class="caption-text"> 深度学习原理：人工神经网络 </span>
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                <a class="reference internal" href="chapter06-01-lab-a-concise-review-and-exemplification-of-deep-learning.html">
                  46. 深度学习综述和示例
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                <a class="reference internal" href="chapter06-02-lab-perceptron-and-artificial-neural-networks.html">
                  47. 感知机和人工神经网络
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                <a class="reference internal" href="chapter06-03-challenge-handwritten-character-recognition-neural-network.html">
                  48. 手写字符识别神经网络
                </a>
              </li>
            </ul>
            <p aria-level="2" class="caption" role="heading">
              <span class="caption-text">
                深度学习框架：TensorFlow &amp; PyTorch
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                <a class="reference internal" href="chapter07-01-lab-tensorflow-fundamentals-and-syntax.html">
                  49. TensorFlow 基础概念语法
                </a>
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                <a class="reference internal" href="chapter07-02-challenge-tensorflow-california-housing-price-prediction.html">
                  50. TensorFlow 加州房价预测
                </a>
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                <a class="reference internal" href="chapter07-03-lab-building-neural-networks-with-tensorflow.html">
                  51. TensorFlow 构建神经网络
                </a>
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              <li class="toctree-l1">
                <a class="reference internal" href="chapter07-04-challenge-tensorflow-automotive-rating-classification.html">
                  52. TensorFlow 汽车评估分类
                </a>
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              <li class="toctree-l1">
                <a class="reference internal" href="chapter07-05-lab-advanced-tensorflow-api-usage.html">
                  53. TensorFlow 高阶 API 使用
                </a>
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              <li class="toctree-l1">
                <a class="reference internal" href="chapter07-06-challenge-tensorflow-fashion-item-classification.html">
                  54. TensorFlow 时尚物品分类
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter07-07-lab-pytorch-fundamentals-and-syntax.html">
                  55. PyTorch 基础概念语法
                </a>
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              <li class="toctree-l1">
                <a class="reference internal" href="chapter07-08-lab-building-neural-networks-with-pytorch.html">
                  56. PyTorch 构建神经网络
                </a>
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                <a class="reference internal" href="chapter07-09-challenge-linear-regression-implementation-with-pytorch.html">
                  57. PyTorch 实现线性回归
                </a>
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            </ul>
            <p aria-level="2" class="caption" role="heading">
              <span class="caption-text"> 深度学习应用：计算机视觉 </span>
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                <a class="reference internal" href="chapter08-01-lab-principles-of-convolutional-neural-networks.html">
                  58. 卷积神经网络原理
                </a>
              </li>
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                <a class="reference internal" href="chapter08-02-lab-convolutional-neural-network-construction.html">
                  59. 卷积神经网络构建
                </a>
              </li>
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                <a class="reference internal" href="chapter08-03-challenge-building-lenet5-estimator.html">
                  60. 构建 LeNet-5 Estimator
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter08-04-lab-principles-and-practices-of-image-classification.html">
                  61. 图像分类原理与实践
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter08-05-challenge-animal-classification-via-transfer-learning.html">
                  62. 迁移学习完成动物分类
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter08-06-lab-principles-and-construction-of-generative-adversarial-networks.html">
                  63. 生成对抗网络原理及构建
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter08-07-challenge-anime-character-image-generation-using-dcgan.html">
                  64. DCGAN 动漫人物图像生成
                </a>
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              <li class="toctree-l1">
                <a class="reference internal" href="chapter08-08-lab-autoencoder-principles-and-construction.html">
                  65. 自动编码器原理及构建
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter08-09-challenge-denoising-convolutional-autoencoders-for-image-denoising.html">
                  66. 卷积自动编码器图像去噪
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter08-10-lab-principles-and-practices-of-object-detection.html">
                  67. 目标检测原理与实践
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter08-11-challenge-yolo-image-object-detection-application.html">
                  68. YOLO 图像目标检测应用
                </a>
              </li>
            </ul>
            <p aria-level="2" class="caption" role="heading">
              <span class="caption-text"> 深度学习应用：自然语言处理 </span>
            </p>
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                <a class="reference internal" href="chapter09-01-lab-principles-of-recurrent-neural-networks.html">
                  69. 循环神经网络原理
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter09-02-lab-construction-of-recurrent-neural-networks.html">
                  70. 循环神经网络构建
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter09-03-challenge-stock-price-prediction-with-lstm.html">
                  71. LSTM 预测股票价格
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter09-04-lab-principles-and-practices-of-text-classification.html">
                  72. 文本分类原理与实践
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter09-05-challenge-deep-learning-for-fake-news-classification.html">
                  73. 深度学习完成假新闻分类
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter09-06-lab-extension-of-natural-language-processing-frameworks.html">
                  74. 自然语言处理框架拓展
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter09-07-challenge-application-of-bert-pretraining-techniques.html">
                  75. Google BERT 预训练技术
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter09-08-lab-neural-machine-translation-and-conversational-systems.html">
                  76. 神经机器翻译和对话系统
                </a>
              </li>
            </ul>
            <p aria-level="2" class="caption" role="heading">
              <span class="caption-text"> 深度学习工程：模型部署和推理 </span>
            </p>
            <ul class="nav bd-sidenav nav sidenav_l1">
              <li class="toctree-l1">
                <a class="reference internal" href="chapter10-01-lab-a-concise-review-of-automated-deep-learning.html">
                  77. 自动化深度学习综述
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter10-02-lab-automated-deep-learning-practice.html">
                  78. 自动化深度学习实践
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter10-03-challenge-aerial-cactus-image-classification.html">
                  79. 仙人掌航拍照片分类识别
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter10-04-lab-deep-learning-model-inference-and-deployment.html">
                  80. 深度学习模型推理和部署
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter10-05-challenge-building-image-classification-inference-service.html">
                  81. 构建图像分类推理服务
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter10-06-lab-deep-learning-cloud-service-practice.html">
                  82. 深度学习云端服务实践
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter10-07-challenge-cloud-service-vat-invoice-recognition.html">
                  83. 云服务识别增值税发票
                </a>
              </li>
            </ul>
            <p aria-level="2" class="caption" role="heading">
              <span class="caption-text"> 强化学习基础 </span>
            </p>
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                <a class="reference internal" href="chapter11-01-lab-introduction-and-examples-of-reinforcement-learning.html">
                  84. 强化学习介绍与示例
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter11-02-lab-implementation-of-the-q-learning-reinforcement-learning-method.html">
                  85. Q-Learning 强化学习方法实现
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="chapter11-03-challenge-implementing-the-sarsa-learning-algorithm-to-navigate-a-maze.html">
                  86. 实现 Sarsa 学习算法走出迷宫
                </a>
              </li>
            </ul>
            <p aria-level="2" class="caption" role="heading">
              <span class="caption-text"> 附录：机器学习数学基础 </span>
            </p>
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              <li class="toctree-l1">
                <a class="reference internal" href="appendix01-01-linear-algebra-with-python.html">
                  87. Python 线性代数基础
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="appendix01-02-calculus-with-python.html">
                  88. Python 微积分基础
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="appendix01-03-probability-theory-and-statistics-with-python.html">
                  89. Python 概率论和统计学基础
                </a>
              </li>
            </ul>
            <p aria-level="2" class="caption" role="heading">
              <span class="caption-text"> 附录：机器学习常用工具 </span>
            </p>
            <ul class="nav bd-sidenav nav sidenav_l1">
              <li class="toctree-l1">
                <a class="reference internal" href="appendix02-00-jupyter-notebook-concise-guide.html">
                  90. Jupyter Notebook 简明指南
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="appendix02-01-numpy-basics-of-numeric-computing.html">
                  91. NumPy 数值计算基础
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="appendix02-02-basic-of-pandas-data-processing.html">
                  92. Pandas 数据处理基础
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="appendix02-03-method-of-drawing-2d-graphics-with-matplotlib.html">
                  93. Matplotlib 二维图像绘制方法
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="appendix02-04-method-of-drawing-3d-graphics-with-matplotlib.html">
                  94. Matplotlib 三维图形绘制方法
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="appendix02-05-introduction-to-seaborn-data-visualization-basics.html">
                  95. Seaborn 数据可视化基础
                </a>
              </li>
              <li class="toctree-l1">
                <a class="reference internal" href="appendix02-06-basic-of-scientific-computing-with-scipy.html">
                  96. SciPy 科学计算基础
                </a>
              </li>
            </ul>
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