B站 - 机器学习必修课：经典AI算法与编程实战 瞿炜

文件内容:

file:03-10Numpy数组矩阵运算：一元运算、二元运算与矩阵运算.mp4
file:03-5JupyterNotebook高级使用：常用魔法命令.mp4
file:03-13Numpy数组神奇索引和布尔索引.mp4
file:02-5机器学习的七大常见误区和局限.mp4
file:03-6Numpy基础：安装与性能对比.mp4
file:03-1本章总览：相互关系与学习路线.mp4
file:01-3课程使用的技术栈.mp4
file:02-4如何分门别类：监督、无监督、强化学习等.mp4
file:03-2Anaconda图形化操作.mp4
file:14-4隐马尔可夫模型代码实现.mp4
file:08-7梯度消失和梯度爆炸.mp4
file:10-1本章总览.mp4
file:09-10SVM优缺点和适用条件.mp4
file:06-7交叉验证.mp4
file:10-2贝叶斯方法核心思想和原理.mp4
file:13-3PCA求解算法.mp4
file:08-9神经网络优缺点和适用条件.mp4
file:11-6串行策略：Boosting.mp4
file:08-6神经网络简单代码实现.mp4
file:07-2决策树核心思想和原理.mp4
file:13-5降维任务代码实现.mp4
file:08-5梯度下降优化算法.mp4
file:09-1本章总览.mp4
file:09-7SVM核函数.mp4
file:10-6贝叶斯方法优缺点和适用条件.mp4
file:09-9SVM回归任务代码实现.mp4
file:08-1本章总览.mp4
file:06-12评价指标：混淆矩阵、精准率和召回率.mp4
file:06-9正则化.mp4
file:09-4SVM软间隔.mp4
folder:B站 - 机器学习必修课：经典AI算法与编程实战 瞿炜