慕课网-Python3入门机器学习 经典算法与应用
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 慕课网-Python3入门机器学习 经典算法与应用https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第3章 Jupyter Notebook ,numpy
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第8章 多项式回归与模型泛化
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第5章 线性回归法
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第4章 最基础的分类算法
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第7章 PCA与梯度上升法
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第12章 决策树
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第9章 逻辑回归
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第6章 梯度下降法
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第11章 支撑向量机SVM
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第13章 集成学习和随机森林
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第14章 更多机器学习算法
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第1章 欢迎来到Python3玩转机器学习
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第2章 机器学习基础
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第10章 评价分类结果
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 github地址.txt
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 Mastering Feature Engineering Principles and Techniques for Data Scientists (Early Release)-O’reilly (2016).pdf
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 ISLR Seventh Printing.pdf
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-4 创建Numpy 数据和矩阵.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-2Jupter Notebook 中的魔法命令.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-11 Matplotlib数据可视化基础.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-10 Numpy中的比较和Fancy lindexing.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-12 数据加载和简单的数据搜索.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-1 Jupyter Notebook基础.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-7 Numpy中的矩阵运算.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-8 Numpy 中的聚合运算.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-5 Numpy数组和矩阵的基本操作.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-6 Numpy 数据和矩阵的合并与分割.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-3 Numpy 数据基础.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-9 Numpy中的arg运算.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-2 scikit-learn 中的多项式回归.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-7 偏差方差平衡.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-6 验证数据集与交叉验证.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-5 学习曲线.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-3 过拟合与欠拟合.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-1 什么是多项式回归.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-10 L1，L2弹性网络.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-4 为什么要训练数据集与测试数据集.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-9 LASSO.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-8 模型泛化与岭回归.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-6 最好的衡量线性回归法的指标.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-8 实现多元线性回归.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-2 最小乘法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-10 线性回归的可解释性.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-4 衡量线性回归的指标.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-5 R Squared.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-9 使用Scilit-learn解决回归问题.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-1 简单线性回归.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-3 简单线性回归的实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-7多元线性回归和正规方程解.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-3 训练数据集.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-8 Scikit-learn中的Scaler.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-1 K近邻算法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-4 分类准确度.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-5 超参数.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-2 scikit-learn机器学习算法封装.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-7 数据归一化.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-9 更多有关K近邻算法的思考.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-6 网络搜索与K邻近算法中更多超参数.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 12-6 - 12-7 .mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 12-3 - 12-5.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 12-1 什么是决策树.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 12-2 信息熵.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-7 试手MNIST数据集.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-9 人脸识别与特征脸.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-5 高纬数据映射为低纬数据.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-3 求数据的主成分.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-6 scikit-learn中的PCA.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-8 使用PCA对数据进行降噪.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-1 什么是PCA.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-2 求数据的主成分PCA问题.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-4 高维数据映射为低维数据（）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-2 逻辑回归的损失函数.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-3 逻辑回归损失函数的梯度.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-5 决策边界.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-1 什么是逻辑回归.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-7 scikt-learn中的逻辑回归.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-8 OvR与OvO.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-4 实现逻辑回归算法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-6 在逻辑回归中使用多项式特征.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-6 随机梯度下降法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-9 有关梯度下降法的更多讨论.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-8有关梯度下降法的更多深入讨论.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-2线性回归中的梯度下降法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-5 梯度下降法的向量化.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-4 实现线性回归中的梯度下降法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-1 什么是梯度下降法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-3实现线性回归中的梯度下降法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-7 scikit-learn中的梯度下降法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-6 什么是核函数.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-8 RBF核函数中的gamma.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-2 svm背后的最优化问题.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-5 SVM中使用多项式特征和核函数.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-3 Soft Margin SVM.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-1 什么是SVM.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-7RBF核函数.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-4 Scikit-learn 中的SVM.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-9 SVM思想解决回归问题.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-2课程涵盖的内容和理念.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-1 什么是机器学习.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-3课程所使用的技术栈.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 14章 学习scikit-learn文档，大家加油！.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 13章.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-2 机器学习的主要任务.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-5 哲学思考.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-3 监督学习、非监督学习....mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-6 课程使用环境搭建.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-1 机器学习的数据.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-4 批量、在线学习、参数、非参数学习.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-6 准确率召回率曲线.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-2 准确率和召回率.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-7 ROC曲线.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-8 多分类问题中的混淆矩阵.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-4 F1 Score.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-5 准确率和召回率的平衡.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-3 现实混淆矩阵.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-1准确度的陷阱和混淆矩阵.mp4
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