ML代码的100天:ML代码的100天中文版-源码

上传者: 42139042 | 上传时间: 2021-02-03 09:38:00 | 文件大小: 44.44MB | 文件类型: ZIP
机器学习100天 英文原版请移步 。数据在。 翻译前请先阅读。常见问题解答见 。 目录 有监督学习 无监督学习 数据预处理|第1天 简单线性回归|第2天 多元线性回归|第3天 逻辑回归|第4天 逻辑回归|第5天 今天我深入研究了逻辑回归到底是什么,以及它背后的数学是什么。学习了如何计算代价函数,以及如何使用渐变下降法来将代价函数降低到最小。由于有人在机器学习领域有一定经验,并愿意帮我编写代码文档,也了解github的Markdown语法,请在领英联系我。 逻辑回归|第6天 K近邻法(k-NN)|第7天 逻辑回归背后的数学|第8天 为了使我对逻辑回归的见解更加清晰,我在网上搜索了一些资源或文章,然后我就发现了Saishruthi Swaminathan的这篇 它称为了逻辑回归的详细描述。请始终看一看。 支持向量机(SVM)|第9天 直观了解SVM是什么以及如何使用它来解决分类问题。 支持向量机和K近邻法|第10天 了解更多关于SVM如何工作和实现knn算法的知识。 K近邻法(k-NN)|第11天 支持向量机(SVM)|第12天 支持向量机(SVM)|第13天 支持向量机(SVM)的实现|

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