B站付费 - 机器学习必修课：经典AI算法与编程实战 瞿炜
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 机器学习必修课：经典AI算法与编程实战https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 12-2聚类算法核心思想和原理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 04-6超参数.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-5多项式朴素贝叶斯代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 07-8决策树优缺点和适用条件.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 03-9Numpy非常重要的数组合并与拆分操作.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 09-3硬间隔SVM.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 05-7逻辑回归算法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 05-11线性算法优缺点和适用条件.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 08-1本章总览.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-3集成学习代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-6串行策略：Boosting.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 06-1本章总览.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 08-7梯度消失和梯度爆炸.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 03-2Anaconda图形化操作.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 14-2概率图模型核心思想和原理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 13-4PCA算法代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 15-4交易反欺诈代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 05-4线性回归代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 04-2KNN算法核心思想和原理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 07-1本章总览.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 06-5过拟合与欠拟合.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-1本章总览.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-2集成学习核心思想和原理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 04-1本章总览.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 04-3KNN分类任务代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 06-10LASSO和岭回归代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 06-9正则化.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 01-2初识机器学习.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 05-1本章总览.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 09-9SVM回归任务代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 09-4SVM软间隔.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 07-7决策树回归任务代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 06-11模型泛化.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 14-4隐马尔可夫模型代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 09-2SVM核心思想和原理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 02-1本章总览.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 08-2神经网络核心思想和原理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 09-5线性SVM分类任务代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 13-5降维任务代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 08-4正向传播与反向传播.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 03-14Matplotlib数据可视化：基础绘制与设置.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 06-7交叉验证.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 05-10复杂逻辑回归及代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 09-6非线性SVM：核技巧.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 01-3课程使用的技术栈.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 05-3逻辑回归核心思想和原理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-4并行策略：Bagging、OOB等方法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 08-3激活函数.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 06-4决策边界.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 03-7Numpy数组创建：特定数组、等差数组、随机数组.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 04-5模型评价.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-6贝叶斯方法优缺点和适用条件.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 07-6决策树剪枝.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 12-5聚类评估代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 15-1本章总览.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 02-2数据长什么样：常见数据集、典型实例、如何使用.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 05-6多项式回归代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-7结合策略：Stacking方法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-8集成学习优缺点和适用条件.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 06-3梯度下降.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 03-5JupyterNotebook高级使用：常用魔法命令.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 07-5基尼系数.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 03-1本章总览：相互关系与学习路线.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 09-10SVM优缺点和适用条件.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-1本章总览.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 09-8非线性SVM代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 04-8KNN回归任务代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 15-3房价预测.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 15-2泰坦尼克生还预测.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 12-3k-means和分层聚类.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 09-1本章总览.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 13-7PCA在人脸识别中的应用.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 03-13Numpy数组神奇索引和布尔索引.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-3朴素贝叶斯分类.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 13-6PCA在数据降噪中的应用.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 02-5机器学习的七大常见误区和局限.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 03-6Numpy基础：安装与性能对比.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-2贝叶斯方法核心思想和原理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 07-3信息熵.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 09-7SVM核函数.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 08-6神经网络简单代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 07-2决策树核心思想和原理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 13-1本章总览.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 08-5梯度下降优化算法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 12-4聚类算法代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-4朴素贝叶斯的代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 07-4决策树分类任务代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 06-13评价指标：ROC曲线.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 02-3研究哪些问题：分类、回归等.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 03-12Numpy数组arg运算和排序.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 02-4如何分门别类：监督、无监督、强化学习等.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 06-8模型误差.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 03-11Numpy数组统计运算：常用的都在这儿了.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 01-1课程内容和理念.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 04-7特征归一化.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 13-3PCA求解算法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 04-4数据集划分：训练集与预测集.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 05-8线性逻辑回归代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 05-9多分类策略.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 06-6学习曲线.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 06-2损失函数.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 06-12评价指标：混淆矩阵、精准率和召回率.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 14-3EM算法参数估计.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 05-5模型评价：MSE、RMSE、MAE和R方.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 05-2线性回归核心思想和原理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 12-6聚类算法优缺点和适用条件.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 13-8主成分分析优缺点和适用条件.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 08-8模型选择.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 13-2PCA核心思想和原理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-5并行策略：随机森林.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 03-4JupyterNotebook基础使用.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 12-1本章总览.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 04-9KNN优缺点和适用条件.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 03-3Anaconda命令行操作.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 03-8Numpy数组基础索引：索引和切片.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 03-10Numpy数组矩阵运算：一元运算、二元运算与矩阵运算.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 14-1本章总览.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 14-5概率图模型优缺点和适用条件.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 15-5如何深入研究机器学习.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 08-9神经网络优缺点和适用条件.mp4
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