What is Learning to Rank? Learning to Rank (LTR) applies machine learning to search relevance ranking. How does relevance ranking differ from other machine learning problems? Regression is one classic machine learning problem. In regression, you’re attem
这个httpoxy漏洞，简单来说，就是可以截获用户http请求包，从而获取到一些敏感信息。 httpoxy简单理解 https://blog.csdn.net/zuoside__lord/article/details/107696503 NC监听 https://blog.csdn.net/qq_34640691/article/details/115740809?utm_medium=distribute.pc_relevant_
https://blog.csdn.net/weixin_44662991/article/details/114144108?utm_medium=distribute.pc_relevant.none-task-blog-2~default~OPENSEARCH~default-13.no_search_link&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2~default~OPENSEARCH~default-13.no
比较经典的棋盘模型，但是确实没想到。 首先，对坐标离散化，那么最多就只剩n行，n列。 然后对于每个棋子(x,y)让x行对y列连边，容量为1，代价 = i. 然后考虑s = 0行,e = 0列。 因为我们要从s出发到e。 那么限制就是从i - 1连到i行，i列连到i - 1列。 https://blog.csdn.net/tianwei0822/artic
转载链接 https://blog.csdn.net/A13777852949/article/details/117334081?utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7ECTRLIST%7Edefault-1.no_search_link&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7ECTRLIST%7Edefau
目录 1、鼠标点上去的时候会有提示 2、自动导入项目所需要的库 3、适用于开发者的界面（设不设置无所谓） 4、显示行号/对方法进行分隔 5、忽略大小写的设置 6、页面视图的展示 7、设置注释的颜色 8、设置编码格式 9、自动编译项目 10、冲突快捷键（代码自动补全）的修改 11、Maven配
链接地址：https://blog.csdn.net/qq_39211866/article/details/85178707?utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7Edefault-14.control&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommend
这里写目录标题 1 人生感悟2 算法技能 1 人生感悟 2 算法技能 【经验分享】我的数据挖掘竞赛之路及秋招总结_abcdefg90876的博客-CSDN博客 https://blog.csdn.net/abcdefg90876/article/details/110789912?utm_medium=distribute.pc_relevant.none-task-blog-2defaultbai
https://blog.csdn.net/qq_34664239/article/details/79106570?utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromMachineLearnPai2%7Edefault-1.control&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCo
cell.showMoreBlock = ^{ // @StrongObj(self); [UIView performWithoutAnimation:^{ [tableView reloadRowsAtIndexPaths:[NSArray arrayWithObjects:indexPath,nil] withRowAnimation:UITableViewRowAnimationNone]; }]; };
https://blog.csdn.net/qq_35310623/article/details/100517269?utm_medium=distribute.pc_relevant_t0.none-task-blog-2%7Edefault%7EBlogCommendFromMachineLearnPai2%7Edefault-1.essearch_pc_relevant&depth_1-utm_source=distribute.pc_relevant_t0.none-task-blog-
https://blog.csdn.net/wz1226864411/article/details/77934941?utm_medium=distribute.pc_relevant.none-task-blog-2~default~BlogCommendFromBaidu~default-8.control&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2~default~BlogCommendFromBaidu~defau
Xshell 远程连接阿里云Linux 服务器:https://blog.csdn.net/weixin_42119415/article/details/83216793?utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromMachineLearnPai2%7Edefault-2.control&depth_1-utm_source=distribute.pc_relevant.none-
MAC下git自动补全功能： https://blog.csdn.net/tiancaijyy/article/details/84888868?utm_medium=distribute.pc_relevant_t0.none-task-blog-2%7Edefault%7EBlogCommendFromMachineLearnPai2%7Edefault-1.base&depth_1-utm_source=distribute.pc_relevant_t0.none-task-blog-2%7
springboot 快速集成guava https://blog.csdn.net/a67474506/article/details/52608855?utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromMachineLearnPai2%7Edefault-4.control&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2
转载： https://libiao.blog.csdn.net/article/details/103722937?utm_medium=distribute.pc_relevant_t0.none-task-blog-BlogCommendFromMachineLearnPai2-1.control&depth_1-utm_source=distribute.pc_relevant_t0.none-task-blog-BlogCommendFromMachineLearnPai2-1.cont
DDM DDM的思想也很简单，就是control the online error-rate of the algorithm（控制算法的在线错误率）。如果样本数据是稳定分布的，那么随着数据的输入，模型的错误率就会逐渐下降；当概率分布发生变化时，模型的错误率就会上升。所以DDM就是在线控制模型训练过程中的错误率。 DDM会为错误率
里面讲得很详细通俗易懂 https://linus.blog.csdn.net/article/details/118864944?utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromMachineLearnPai2%7Edefault-10.control&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefau
https://blog.csdn.net/qq_41809137/article/details/98464525?utm_medium=distribute.pc_relevant_t0.none-task-blog-2%7Edefault%7EBlogCommendFromMachineLearnPai2%7Edefault-1.control&depth_1-utm_source=distribute.pc_relevant_t0.none-task-blog-2%7Edefault%7E
https://blog.csdn.net/weixin_33754065/article/details/85981556?utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromMachineLearnPai2%7Edefault-1.control&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBl
摘要：物理机安装kafka:https://blog.csdn.net/qq_31851107/article/details/109778056?utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7Edefault-1.control&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBl
//太难了，没看懂 //可以参考https://zhanglong.blog.csdn.net/article/details/104831434?utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EOPENSEARCH%7Edefault-3.readhide&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EOPENSEA
https://blog.csdn.net/WHAT_IS_THE_NAME/article/details/97957169?utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromMachineLearnPai2%7Edefault-1.control&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EB
https://blog.csdn.net/qq_35733535/article/details/109227358?utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromMachineLearnPai2%7Edefault-3.control&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogC
PCA过程解释: https://blog.csdn.net/lanyuelvyun/article/details/82384179?utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromMachineLearnPai2%7Edefault-1.control&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edef
