<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[鸣一的专栏]]></title><description><![CDATA[专注于机器学习，大数据]]></description><link>https://blog.youkuaiyun.com/mdming412</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; mdming412]]></copyright><item><title><![CDATA[启动audit服务报错]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/132479137</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/132479137</guid><author>mdming412</author><pubDate>Thu, 24 Aug 2023 17:36:51 +0800</pubDate><description><![CDATA[【代码】启动audit服务报错。]]></description><category></category></item><item><title><![CDATA[ssh失败：ssh_exchange_identification: read: Connection reset by peer]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/131458376</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/131458376</guid><author>mdming412</author><pubDate>Thu, 29 Jun 2023 16:14:49 +0800</pubDate><description><![CDATA[ssh_exchange_identification: read: Connection reset by peer]]></description><category></category></item><item><title><![CDATA[记一次Macbook pro电池修复]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/130310273</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/130310273</guid><author>mdming412</author><pubDate>Sat, 22 Apr 2023 21:07:46 +0800</pubDate><description><![CDATA[macbook pro电池修复]]></description><category></category></item><item><title><![CDATA[Springboot No qualifying bean of type ‘xxx.xxx‘ available]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/129118681</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/129118681</guid><author>mdming412</author><pubDate>Mon, 20 Feb 2023 09:52:38 +0800</pubDate><description><![CDATA[对相应的实现mapper类 添加@Mapper 标记。原因：没有将相关类注入到springboot。]]></description><category></category></item><item><title><![CDATA[kafka-consumer-groups.sh error :Failed to find brokers to send ListGroups]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/128691597</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/128691597</guid><author>mdming412</author><pubDate>Sun, 15 Jan 2023 08:45:19 +0800</pubDate><description><![CDATA[执行kafka 脚本 ,无法看查看消费组，报错 Failed to find brokers to send ListGroups。]]></description><category></category></item><item><title><![CDATA[kafka开kerberos认证报错the client is being asked for a password]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/128690345</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/128690345</guid><author>mdming412</author><pubDate>Sat, 14 Jan 2023 22:58:00 +0800</pubDate><description><![CDATA[在Kafka工程 且开 kerberos 时，遇到报错：Could not login: the client is being asked for a password, but the Kafka client code does not currently support obtaining a password from the user. ]]></description><category></category></item><item><title><![CDATA[AlphaGo Zero 总结]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/78305085</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/78305085</guid><author>mdming412</author><pubDate>Sat, 21 Oct 2017 17:29:03 +0800</pubDate><description><![CDATA[参考了各教授对AlphaGo Zero的分析，整理笔记如下：
3天内——AlphaGo Zero进行过490万次自我对弈练习，并干掉AlphaGo Lee，这说明模型训练速度干净，准确，没有在那里玩太极。
强化学习 Policy network 和 value network 整合在一起，结构更简洁；共享参数，效率更高。 
两个核心要素  :  一个是启发式搜索，一个是深度残差神经网络，而这两者又实]]></description><category></category></item><item><title><![CDATA[如何理解“七日年化收益率”]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/78304844</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/78304844</guid><author>mdming412</author><pubDate>Sat, 21 Oct 2017 17:00:45 +0800</pubDate><description><![CDATA[七日年化收益率]]></description><category></category></item><item><title><![CDATA[项目管理学习笔记]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/52565639</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/52565639</guid><author>mdming412</author><pubDate>Sun, 18 Sep 2016 00:04:44 +0800</pubDate><description><![CDATA[项目管理学习笔记
项目计划 
明确项目有哪些具体工作要做（任务break down） 
各项工作有需花多少时间完成，标注好起始，结束时间; 
定好工作的优先级，或次序 
谁来完成哪些工作 
各项工作花费多少成本，整个项目总成本是多少]]></description><category></category></item><item><title><![CDATA[Python 个人学习笔记]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/52348623</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/52348623</guid><author>mdming412</author><pubDate>Sat, 17 Sep 2016 21:29:29 +0800</pubDate><description><![CDATA[本篇个人笔记仅个人，未必适合众友。获取帮助 
1.通过Python解释器获取帮助。 
2.调用help(object) 
3.dir(object) 会显示该对象的所有方法， 
4 . >>>object.__doc__  #" __doc__"会显示其文档, 有些基础用法，网友总结得很好： 
http://chuansong.me/n/1762453 【十分钟学会 Python】好玩的python]]></description><category></category></item><item><title><![CDATA[scikit-learn 学习笔记]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/52344637</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/52344637</guid><author>mdming412</author><pubDate>Sun, 28 Aug 2016 12:52:41 +0800</pubDate><description><![CDATA[scikit-learn 学习笔记关于数据集dataset 
1. 可以查看官网的描述 ： http://scikit-learn.org/stable/datasets/index.html 
2. 也可以 直接看source code.load_boston()   #Load and return the boston house-prices dataset (regression).
lo]]></description><category></category></item><item><title><![CDATA[Numpy 的常用函数[学习笔记]]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/52338239</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/52338239</guid><author>mdming412</author><pubDate>Sun, 28 Aug 2016 11:56:09 +0800</pubDate><description><![CDATA[Numpy 的常用函数First of all : from numpy import *arr1=random.rand(4,4)   #构造 4*4 array
mat1=mat(random.rand(4,4)) #mat() 将数组转成matrix
arr1.shape         #查看数组，或矩阵的大小、或维数
arr1.I            #矩阵求逆
data1.dtype]]></description><category></category></item><item><title><![CDATA[scikit-learn digital write recognize]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/52337639</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/52337639</guid><author>mdming412</author><pubDate>Sat, 27 Aug 2016 23:29:37 +0800</pubDate><description><![CDATA[【笔记】调一下scikit-learn ： 
详细链接：http://xhrwang.me/2015/02/13/scikit_learn-tutorial.html下面的例子将演示如何使用 sklearn 库中提供的数字图片 dataset 来识别它们表示的实际数字, 且标记本人的一些学习心得。所需lib:  matplotlib.pyplot & sklearn 
数据源：sklearn.dat]]></description><category></category></item><item><title><![CDATA[IPython magic function - 测试代码运行时间]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/52334579</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/52334579</guid><author>mdming412</author><pubDate>Sat, 27 Aug 2016 12:47:16 +0800</pubDate><description><![CDATA[IPython 测试程序运行时间%time 代码片段/ 程序名针对 微秒级（1e-6） 和纳秒级（1e-9） 
%timeit   代码片段/ 程序名基本性能分析[宏观]： 
%prun%run -p逐行分析函数性能[微观] 
%lprun -f func1 -f func2  statement.py%lprun]]></description><category></category></item><item><title><![CDATA[IPython 交互式调试器]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/52334525</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/52334525</guid><author>mdming412</author><pubDate>Sat, 27 Aug 2016 12:23:55 +0800</pubDate><description><![CDATA[IPython 交互式debug增强pdb ,语法高亮，tab 自动补全【debug时机是刚出现异常那会】%debug  
u    #跟踪栈在各级间的切换
d设置断点单步调度  
%run -d script.pys 进入脚本 ， 
b 13  # 在13行设置断点 
c  # continue till touch the break point 
n # 执行下一行。 
如果有exceptio]]></description><category></category></item><item><title><![CDATA[Ipython 操作shell]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/52334110</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/52334110</guid><author>mdming412</author><pubDate>Sat, 27 Aug 2016 10:55:01 +0800</pubDate><description><![CDATA[在ipython的输入端，进行Shell命令的执行IPython中可以执行cd ls 等常见的命令，执行shell的其他命令时在命令前加感叹号( ! )In [1]:!ping 192.168.1.4PING 192.168.1.4 (192.168.1.4) 56(84) bytes of data. 
64 bytes from 192.168.1.4: icmp_req=1 ttl=252 t]]></description><category></category></item><item><title><![CDATA[Ipython magic function]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/52334096</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/52334096</guid><author>mdming412</author><pubDate>Sat, 27 Aug 2016 10:48:42 +0800</pubDate><description><![CDATA[概率分布学习笔记(注：部分资料源自他人博客)
离散型和连续型随机变量的定义
离散型随机变量（discrete random variable）：取值是可数的个值的随机变量， 比如投掷一枚骰子的朝上的点数，可能是1,2,3,4,5,6；比如南京大学四食堂吃饭的人数，可能是0,1,2···。  
连续型随机变量（continuous random variable）：取值是一个区间中的任意一点（也就是不]]></description><category></category></item><item><title><![CDATA[Shell 处理命令行参数 getopts 和 getopt]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/52198510</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/52198510</guid><author>mdming412</author><pubDate>Sun, 14 Aug 2016 10:11:26 +0800</pubDate><description><![CDATA[Shell 处理命令行参数 getopts 和 getopt在处理复杂参数选项的时候常用的两种方法：
getopts -Bash内置  ；简单
getopt - 独立的可执行文件 ; 强大
===========
getopts 简单用法
#!/bin/bashwhile getopts "h:f1:f2" arg #选项后面的冒号表示该选项需要参数
do
        case $arg in]]></description><category></category></item><item><title><![CDATA[shell 传参sed]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/52198341</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/52198341</guid><author>mdming412</author><pubDate>Sat, 13 Aug 2016 11:19:00 +0800</pubDate><description><![CDATA[shell 传参sed在shell 传参给sed 时，会失效，原因是单引号” ,它会阻止转义 。 
So  把单引号改为 双引号 “” ,就OK 了。举个栗子：#!/bin/shsessionID=$1
echo "Usage: pplog.sh $sessionID "#Test1 :correct sample
sed -n "/${sessionID}-START/,/${sessionID}]]></description><category></category></item><item><title><![CDATA[机器基石笔记摘要]]></title><link>https://blog.youkuaiyun.com/mdming412/article/details/52197636</link><guid>https://blog.youkuaiyun.com/mdming412/article/details/52197636</guid><author>mdming412</author><pubDate>Sat, 13 Aug 2016 11:06:58 +0800</pubDate><description><![CDATA[机器基石笔记摘要机器基石034个基本模式 （在输出空间）：
Binary classify (二分类 ，是非题) 
      Y={-1,+1}
Multiple classify  
      Y={1,2,3,…. , k}
Regression 
     Y=R
Structured Learning: Sequence Tagging Problem （马尔可夫链） 
    Y=st]]></description><category></category></item></channel></rss>