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Home Page: http://doudou0o.github.io
It is my blog!
Home Page: http://doudou0o.github.io
https://www.doudou0o.com/archives/1cbdb2f8.html
魔兽争霸重制版来了,从官网盗了几张图~
https://www.doudou0o.com/archives/b6159bfb.html
倒腾了很久 Jekyll 之后,还是决定投入到 Hexo 阵营中来。Hexo的 markdown 编译器以及优秀的各种模板还有一键部署都是相当赞的功能。由于我也是新手白菜,记录本篇搭建日志,以防遗忘和换些功能或模板设置。
https://www.doudou0o.com/archives/fe118cd8.html
讨论在多进程环境下如何使用logging来输出日志,如何安全地切分日志文件
https://www.doudou0o.com/archives/45aaf959.html
数据和特征决定了机器学习的上限,而模型和算法只是逼近这个上限而已!回顾及沉淀一下特征处理相关的知识和基础
https://www.doudou0o.com/archives/d5955c4c.html
前段时间有小伙伴问了我好几次中文切词是怎么切的,我想着应该是我没表达清楚所以小伙伴才会重复问多次,是我表达能力不够,临时说也说不上来。所以就写一篇了简单的中文切词方法的短文,一方面是锻炼下自己的表达能力,另一方面下次小伙伴再问就直接扔给他Y(^o^)Y
https://www.doudou0o.com/archives/4cc8a378.html
数据和特征决定了机器学习的上限,而模型和算法只是逼近这个上限而已!无量纲化能提升特征可比性,优化训练时间;哑编码能降低模型复杂度,提升特征表达能力,提升运算时间,提升非线性能力。
https://www.doudou0o.com/archives/f4d50b3c.html
Never forget what you are, for surely the world will not. Make it your strength. Then it can never be your weakness. Armor yourself in it, and it will never be used to hurt you.
https://www.doudou0o.com/archives/a06283d5.html
数据和特征决定了机器学习的上限,而模型和算法只是逼近这个上限而已!很多情况下,数据总有可能缺失,但是若是放任不管可能造成严重的后果甚至模型无法收敛,所以我们得利用已有的信息进行数据填充来降低损失。特征组合是将不同的特征进行组合,生成新的特征,这种方式能提升模型更大的非线性能力和拟合能力。
https://www.doudou0o.com/archives/efc41243.html
在工作中,经常遇到很多事情会涉及到算法机器学习,然而似乎有不少人会对算法亦或是机器学习有着这样那样的误解。于是我准备收拾一下,机器学习的基础知识,以辅助大家了解机器学习,知道机器学习是干什么的,它又是怎么工作的。
https://www.doudou0o.com/archives/2456c8ba.html
在求解函数最优化问题中,拉格朗日乘子法(Lagrange Multiplier)和KKT(Karush Kuhn Tucker)条件是两种最常用的方法。函数有等式约束时使用拉格朗日乘子法,函数有不等约束时使用KKT条件。本文简要的复习下拉格朗日乘数法的浅层次问题。
https://www.doudou0o.com/archives/a66e40a.html
隐马尔科夫模型是一种统计模型,他由马尔科夫随机过程生成无法观察的状态随机序列,每个状态又会生成不同的观测值,从而产生随机观测序列。
https://www.doudou0o.com/archives/45aaf959.html
数据和特征决定了机器学习的上限,而模型和算法只是逼近这个上限而已!
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