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mkdocs.yml
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site_name: ai课程参考资料
nav:
- 前言: index.md
- 机器学习基础:
- 机器学习入门:
- 机器学习入门: 201-ml-intro.md
- 基本概念:
- 机器学习简介: 201-ml-basics/201-ml-intro-basics-01.md
- 线性回归: 201-ml-basics/201-ml-intro-basics-02.md
- logitstic回归: 201-ml-basics/201-ml-intro-basics-03.md
- 损失: 201-ml-basics/201-ml-intro-basics-04.md
- 梯度下降: 201-ml-basics/201-ml-intro-basics-05.md
- 正则化/weight decay: 201-ml-basics/201-ml-intro-basics-06.md
- 应用技巧:
- 非均衡数据: 201-ml-basics/201-ml-intro-skills-07.md
- Hard-Example: 201-ml-basics/201-ml-intro-skills-08.md
- Early Stop: 201-ml-basics/201-ml-intro-skills-09.md
- 机器学习基础算法:
- 支持向量机: 202-ml-basics/202-ml-basics-01.md
- 决策树: 202-ml-basics/202-ml-basics-02.md
- 随机森林: 202-ml-basics/202-ml-basics-03.md
- GBDT: 202-ml-basics/202-ml-basics-04.md
- PCA: 202-ml-basics/202-ml-basics-05.md
- 聚类算法: 202-ml-basics/202-ml-basics-06.md
- 吸引力传播: 404.md
- 集成学习: 202-ml-basics/202-ml-basics-07.md
- 优化算法: 202-ml-basics/202-ml-basics-08.md
- 机器学习算法进阶:
- 异常检测: 203-ml-advance/203-ml-advance-03.md
- 最大期望算法: 404.md
- 深度学习入门:
- 深度学习入门: 211-dl-intro.md
- 深度学习基础: 211-dl-intro/211-dl-intro-01.md
- 深度学习历史发展: 211-dl-intro/211-dl-intro-02.md
- 感知器与优化规则: 211-dl-intro/211-dl-intro-03.md
- 异或问题: 211-dl-intro/211-dl-intro-04.md
- 神经网络简介: 211-dl-intro/211-dl-intro-05.md
- 全连接网络: 211-dl-intro/211-dl-intro-06.md
- 深度学习基础算法:
- 深度学习基础算法: 212-dl-basics.md
- 基础算法:
- 神经网络前向传播: 212-dl-basics/212-dl-basics-01.md
- 神经网络拟合数据: 212-dl-basics/212-dl-basics-02.md
- 神经网络反向传播: 212-dl-basics/212-dl-basics-03.md
- 调参:
- 过拟合与欠拟合: 212-dl-basics/212-dl-basics-04.md
- 学习率/lr decay: 212-dl-basics/212-dl-basics-05.md
- 优化算法：动量: 212-dl-basics/212-dl-basics-06.md
- 正则化: 212-dl-basics/212-dl-basics-07.md
- 进一步讨论损失函数: 212-dl-basics/212-dl-basics-08.md
- 进一步讨论激活函数: 212-dl-basics/212-dl-basics-09.md
- 参数的初始化: 212-dl-basics/212-dl-basics-10.md
- batch norm: 212-dl-basics/212-dl-basics-11.md
- dropout: 212-dl-basics/212-dl-basics-12.md
- 蒸馏法/transfer learning: 212-dl-basics/212-dl-basics-13.md
- 深度置信网络: 212-dl-basics/212-dl-basics-14.md
- 自编码器: 212-dl-basics/212-dl-basics-15.md
- 视觉:
- 计算机视觉基础:
- 视觉介绍:
- 动物视觉介绍: 301-cv-basics/301-cv-basics-01.md
- 计算机视觉介绍: 301-cv-basics/301-cv-basics-02.md
- 视觉系统: 301-cv-basics/301-cv-basics-03.md
- 视觉认知: 301-cv-basics/301-cv-basics-04.md
- 数字图像基础:
- 图像信号的数学表示: 301-cv-basics/301-cv-basics-05.md
- 图像的采样和量化: 301-cv-basics/301-cv-basics-06.md
- 像素连通性: 301-cv-basics/301-cv-basics-07.md
- rgb/bgr/lab/yuv/hsv/cmy及换算公式: 301-cv-basics/301-cv-basics-08.md
- 视频压缩与图像显示: 301-cv-basics/301-cv-basics-09.md
- 图像的线性系统理论: 301-cv-basics/301-cv-basics-10.md
- 常用CV算法:
- 图像处理与变换:
- 二维傅立叶变换及其基本性质: 302-cv-algorithms/302-cv-algorithms-01.md
- 快速傅立叶变换: 302-cv-algorithms/302-cv-algorithms-02.md
- 离散小波变换: 302-cv-algorithms/302-cv-algorithms-03.md
- 象素间的连通性: 302-cv-algorithms/302-cv-algorithms-04.md
- 灰度/彩色直方图: 302-cv-algorithms/302-cv-algorithms-05.md
- 图像空域滤波技术: 302-cv-algorithms/302-cv-algorithms-06.md
- 图像频域滤波: 302-cv-algorithms/302-cv-algorithms-07.md
- 多光谱图像处理: 302-cv-algorithms/302-cv-algorithms-08.md
- 颜色特征的图像检索: 302-cv-algorithms/302-cv-algorithms-09.md
- 图像金字塔: 302-cv-algorithms/302-cv-algorithms-10.md
- 二值化/大津算法/开闭操作: 302-cv-algorithms/302-cv-algorithms-11.md
- 边缘检测：sobel/laplance/canny: 302-cv-algorithms/302-cv-algorithms-12.md
- 泛洪填充: 302-cv-algorithms/302-cv-algorithms-13.md
- 视觉几何基础:
- 坐标系与坐标变化: 302-cv-algorithms/302-cv-algorithms-14.md
- 多视角: 302-cv-algorithms/302-cv-algorithms-15.md
- 标定: 302-cv-algorithms/302-cv-algorithms-16.md
- 双目与景深: 302-cv-algorithms/302-cv-algorithms-17.md
- 哈夫变换: 302-cv-algorithms/302-cv-algorithms-18.md
- 姿态与空间重建/多图使用: 302-cv-algorithms/302-cv-algorithms-19.md
- 视觉认知模型:
- 微分算子: 302-cv-algorithms/302-cv-algorithms-20.md
- 阈值分割: 302-cv-algorithms/302-cv-algorithms-21.md
- 区域生长: 302-cv-algorithms/302-cv-algorithms-22.md
- 评价测度: 302-cv-algorithms/302-cv-algorithms-23.md
- 图搜索: 302-cv-algorithms/302-cv-algorithms-24.md
- 动态规划: 302-cv-algorithms/302-cv-algorithms-25.md
- 灰度共生矩阵: 302-cv-algorithms/302-cv-algorithms-26.md
- 基于模型的纹理分析: 302-cv-algorithms/302-cv-algorithms-27.md
- 运动估计简介/跟踪: 302-cv-algorithms/302-cv-algorithms-28.md
- 光流法: 302-cv-algorithms/302-cv-algorithms-29.md
- 识别与高层认知:
- 图像的特征点: 302-cv-algorithms/302-cv-algorithms-30.md
- Harris算法: 302-cv-algorithms/302-cv-algorithms-31.md
- SIFT/SURF算法: 302-cv-algorithms/302-cv-algorithms-32.md
- HOG算子检测: 302-cv-algorithms/302-cv-algorithms-33.md
- 距离: 302-cv-algorithms/302-cv-algorithms-34.md
- 统计分类方法: 302-cv-algorithms/302-cv-algorithms-35.md
- 马尔科夫随机场: 302-cv-algorithms/302-cv-algorithms-36.md
- 条件随机场: 302-cv-algorithms/302-cv-algorithms-37.md
- 模板匹配: 302-cv-algorithms/302-cv-algorithms-38.md
- 目标匹配: 302-cv-algorithms/302-cv-algorithms-39.md
- 特征内容匹配: 302-cv-algorithms/302-cv-algorithms-40.md
- Marr视觉计算理论: 302-cv-algorithms/302-cv-algorithms-41.md
- 应用:
- 多序列的三维重建: 302-cv-algorithms/302-cv-algorithms-42.md
- 数字图书馆藏查询: 302-cv-algorithms/302-cv-algorithms-43.md
- OpenCV:
- opencv简介: 303-cv-opencv/303-cv-opencv-01.md
- 不同操作系统下的OpenCV安装教程: 303-cv-opencv/303-cv-opencv-02.md
- 图片存取与显示: 303-cv-opencv/303-cv-opencv-03.md
- 颜色转换: 303-cv-opencv/303-cv-opencv-04.md
- 各经典算法的api及文档导读: 303-cv-opencv/303-cv-opencv-05.md
- Visual Studio 2019 Community下源码编译OpenCV 3.4.1: 303-cv-opencv/303-cv-opencv-06.md
- 计算机视觉与神经网络:
- 卷积神经网络:
- 卷积计算: 311-cv-nn/311-cv-nn-01.md
- 初始化: 311-cv-nn/311-cv-nn-02.md
- 传统卷积使用: 311-cv-nn/311-cv-nn-03.md
- 卷积神经网络介绍: 311-cv-nn/311-cv-nn-04.md
- 池化: 311-cv-nn/311-cv-nn-05.md
- 特征的使用: 311-cv-nn/311-cv-nn-06.md
- 业务网络设计: 311-cv-nn/311-cv-nn-07.md
- 分类器的概念: 311-cv-nn/311-cv-nn-08.md
- 卷积神经网络案例:
- VGG: 311-cv-nn/311-cv-nn-09.md
- GoogleLeNet: 311-cv-nn/311-cv-nn-10.md
- resnet: 311-cv-nn/311-cv-nn-11.md
- densenet: 311-cv-nn/311-cv-nn-12.md
- nasnet: 311-cv-nn/311-cv-nn-13.md
- se-net: 311-cv-nn/311-cv-nn-14.md
- MobileNet v1/v2: 311-cv-nn/311-cv-nn-15.md
- 已被证明有效的基础模块: 311-cv-nn/311-cv-nn-16.md
- 卷积神经网络应用:
- 分类: 311-cv-nn/311-cv-nn-17.md
- 检测: 311-cv-nn/311-cv-nn-18.md
- 分割: 311-cv-nn/311-cv-nn-19.md
- 人脸: 311-cv-nn/311-cv-nn-20.md
- 各种娱乐项目（style transher/deepdream/nima/gan）: 311-cv-nn/311-cv-nn-21.md
- backbone: 311-cv-nn/311-cv-nn-22.md
- 自然语言处理NLP: 321-nlp-intro.md
- 附录:
- 符号约定: notation.md
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