December 2019
Intermediate
7h 14m
Chinese
Overview
课程简介
6小时以上的视频教学
通过scikit-learn中包含的大量示例代码来学习现代机器学习中的主要概念和技术
“通过课程中的Jupyter Notebook的代码，很好地介绍和概述了scikit-learn库中的API。这非常适合掌握数据科学过程中使用到的技术，提纲挈领。” 5星/5星。
--mazurkrzysztofk，O'Reilly在线学习评论员
Overview
概述
Machine Learning with scikit-learn LiveLessons 是scikit-learn库的指南，该库提供了广泛的机器学习算法，以及通用且直观的相对统一的Python API。
为各种模型提供的几十个类中大多数有着相同的接口。
大多数时候你可以很容易地用一种算法来替换另一种算法，并且几乎不用修改你的代码。
这使你能够快速探索问题空间，并经常可以获得关于你的问题或数据集的最佳的解决方案，或者至少是得到一个令你满意的方案。
scikit-learn库建立在一些数学方面的Python库之上。它使用NumPy进行基本数据结构和性能上的优化，并与pandas和matplotlib兼容。scikit-learn是BSD许可下的免费软件。在深度神经网络这一个细分领域之外，Python中非常多机器学习程序是通过scikit-learn来完成的。
Get技能
• 使用各种机器学习技术
• 探索数据集
• 执行各种分类算法任务
• 使用回归算法，聚类算法和超参数
• 使用特征工程和特征选择
• 实现数据管道（Pipeline）
• 开发稳健的训练集/测试集划分
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