<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[acoco_wang的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/acoco_wang</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; acoco_wang]]></copyright><item><title><![CDATA[java升级遇到的问题]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/104222087</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/104222087</guid><author>acoco_wang</author><pubDate>Sat, 08 Feb 2020 13:33:13 +0800</pubDate><description><![CDATA[1.oracel 官网下载jdk11
2.jre文件包 通过在cmd（！！！进入管理原权限）中运行 bin\jlink …… 命令生成
3.环境配置正确
4.java -version   javac -version  set  path   等进行查看
5.删除 regit表中的之前java版本
6.可以将 path中java 环境变量上移 排除问题

...]]></description><category></category></item><item><title><![CDATA[colab中tensorflow 版本]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/103961111</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/103961111</guid><author>acoco_wang</author><pubDate>Mon, 13 Jan 2020 17:07:34 +0800</pubDate><description><![CDATA[问题：tensorflow中之前默认版本是1，tensorflow中tutor是2版本
解决1.修改sys.path
解决2.加载到drive中
https://stackoom.com/question/3y9ll/%E8%BF%90%E8%A1%8C%E6%97%B6%E9%87%8D%E6%96%B0%E5%90%AF%E5%8A%A8%E5%90%8E-Colab%E7%9A%84Tens...]]></description><category></category></item><item><title><![CDATA[安装教程]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/89476352</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/89476352</guid><author>acoco_wang</author><pubDate>Tue, 23 Apr 2019 16:58:48 +0800</pubDate><description><![CDATA[centos 安装python3.6
一般在/opt路径下
参考
https://www.yuzhi100.com/tutorial/centos/centos-anzhuang-python36

]]></description><category></category></item><item><title><![CDATA[win hadoop 安装]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/89454742</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/89454742</guid><author>acoco_wang</author><pubDate>Mon, 22 Apr 2019 16:27:58 +0800</pubDate><description><![CDATA[参考了一下链接，其中还是会出现几个问题，记录一下

用镜像地址下载hadoop安装包会快很多
win下安装需要在hadoop\bin 下添加 hadoop.dll和winunit.exe ，下路径有更全的版本
JAVA_HOME绝对路径有空格 ，可用特殊字符替代  Program Files 替代为PROGRA~1;  相应的Program Files（x86）可替换为 PROGRA ~2

除了...]]></description><category></category></item><item><title><![CDATA[数学基础好的链接]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/88806616</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/88806616</guid><author>acoco_wang</author><pubDate>Mon, 25 Mar 2019 21:27:25 +0800</pubDate><description><![CDATA[极大似然函数
https://blog.youkuaiyun.com/zengxiantao1994/article/details/72787849

]]></description><category></category></item><item><title><![CDATA[学习资源]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/86552942</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/86552942</guid><author>acoco_wang</author><pubDate>Sat, 19 Jan 2019 15:35:24 +0800</pubDate><description><![CDATA[深度学习
1.https://github.com/ageron/tf2_course  使用jupyter精简教程，量子位推荐
2.https://www.dropbox.com/s/v3rq3895r05xick/deep_learning_state_of_the_art.pdf?dl=0    最前沿的深度学习内容  附有ppt
3.伯克利深度学习《动手学深度学习》
新课GitHub传送门...]]></description><category></category></item><item><title><![CDATA[python连接各种数据源]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/85947346</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/85947346</guid><author>acoco_wang</author><pubDate>Sun, 06 Jan 2019 20:17:06 +0800</pubDate><description><![CDATA[本地csv，txt
pandas库 pd.read_csv() pd.to_csv()
with  open()  as f: f.read()/f.write()   ??readline() readlines()
mysql
import pymysql
from sqlalchemy import create_engine
– 读
connection=pymysql.connect(h...]]></description><category></category></item><item><title><![CDATA[决策树]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/82944726</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/82944726</guid><author>acoco_wang</author><pubDate>Sun, 25 Nov 2018 21:25:22 +0800</pubDate><description><![CDATA[ft(x)f_t(x)ft​(x)   ——&amp;amp;amp;gt;    yty_tyt​    ——&amp;amp;amp;gt;  E(损失)=yt∗C+(1−yt)∗C∗RE(损失)=y_t*C+(1-y_t)*C*RE(损失)=yt​∗C+(1−yt​)∗C∗R
C为成本   R 为利息
代入公式中
obj=∑i=0nE(损失)∗L(y,y预测)obj=\sum_{i=0}^nE(损失)*L(y,y_{预测})obj=∑i=...]]></description><category></category></item><item><title><![CDATA[可视化 ，绘图]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/84143418</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/84143418</guid><author>acoco_wang</author><pubDate>Fri, 16 Nov 2018 17:47:28 +0800</pubDate><description><![CDATA[
seaborn库

displot  频数分布图
boxplot



import seaborn as sns
from scipy import norm
import mat…  as plt
sns.displot(array,hist=False,fit=norm)
plt.xtrick(range())
plt.xlable(’’)
plt.show()

...]]></description><category></category></item><item><title><![CDATA[python中解决各种问题]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/84110379</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/84110379</guid><author>acoco_wang</author><pubDate>Thu, 15 Nov 2018 20:26:30 +0800</pubDate><description><![CDATA[
dict的遍历  dict.get()
list 的sort   li=sorted(new_list, key=lambda x:x[1],reverse=True)


]]></description><category></category></item><item><title><![CDATA[dos命令]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/84108660</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/84108660</guid><author>acoco_wang</author><pubDate>Thu, 15 Nov 2018 18:07:21 +0800</pubDate><description><![CDATA[合并多个excel | csv
https://blog.youkuaiyun.com/u014369410/article/details/45598893


]]></description><category></category></item><item><title><![CDATA[特征]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/83959464</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/83959464</guid><author>acoco_wang</author><pubDate>Sun, 11 Nov 2018 16:13:29 +0800</pubDate><description><![CDATA[
数据清洗
数据规范化处理
特征衍生与提取

特征选择
4. 特征过滤
5. wrapper
6. enbedded
填充 ：
0     pandas  data.fillna(0)
均值、中位数、频数   data.fillna(data.mean()\median())    结果粗糙
最大最小
序号相邻 data.fillna(method=‘bfill’)
相似性（k最近邻）
线性回归填...]]></description><category></category></item><item><title><![CDATA[MySQL&Hive]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/83933047</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/83933047</guid><author>acoco_wang</author><pubDate>Sat, 10 Nov 2018 20:53:14 +0800</pubDate><description><![CDATA[python连接
支持python3的为  PyMySQL
入门操作教程
21分钟
http://www.cnblogs.com/mr-wid/archive/2013/05/09/3068229.html
安装WorkBench
https://www.jianshu.com/p/6f7f61317f52
修改root密码，一般设置123456
https://www.linuxidc.com/...]]></description><category></category></item><item><title><![CDATA[推荐]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/83870164</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/83870164</guid><author>acoco_wang</author><pubDate>Thu, 08 Nov 2018 23:06:17 +0800</pubDate><description><![CDATA[协同过滤算法
比较好的一些阅读资料

code https://github.com/ThomasHuai/Recommend
原理详解 http://python.jobbole.com/86563/
实战  电影预测 https://github.com/ThomasHuai/Recommend
SVD应用于推荐算法，矩阵秩 https://blog.youkuaiyun.com/zhongkejingw...]]></description><category></category></item><item><title><![CDATA[爬虫]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/83869125</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/83869125</guid><author>acoco_wang</author><pubDate>Thu, 08 Nov 2018 21:49:45 +0800</pubDate><description><![CDATA[从地址信息提炼省、市
用了re  正则表达式   “.*省（\w+）市”   ‘（\w+）市&quot;
后来发现现成python库 ‘cpca’  可以直接transfer

]]></description><category></category></item><item><title><![CDATA[内存和CPU占用率过高，该怎么办？]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/83378860</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/83378860</guid><author>acoco_wang</author><pubDate>Thu, 25 Oct 2018 14:16:51 +0800</pubDate><description><![CDATA[转载自戴尔 公众号
戴尔  今天
“
电脑的内存和CPU都达到非常大的占用率时
就很可能会导致系统崩溃
”
本期视频中，小编将指导大家如何尽量有效的减少内存和CPU的占用率。
尝试进行ePSA硬件检测。关机重启，开机在看到Dell Logo后，多次敲击F12进入ePSA界面。选择Diagnostics，敲击回车键进行硬件检测。若检测出问题，那么建议您联系我们的技术支持人员，若未检测出问题，那么尝试...]]></description><category></category></item><item><title><![CDATA[整理数据挖掘类期刊会议]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/83011891</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/83011891</guid><author>acoco_wang</author><pubDate>Thu, 11 Oct 2018 14:25:27 +0800</pubDate><description><![CDATA[杂志
KDD(1991)  Knowledge Discovery in Databases
AKDDM(1996) Advances in Knowledge Discovery and Data Mining
JDMKD(1997) Journal of Data Mining and Knowledge Discovery
PAKDD(1997) PKDD(1997) SIAM-Data M...]]></description><category></category></item><item><title><![CDATA[分享交流整理]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/82914258</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/82914258</guid><author>acoco_wang</author><pubDate>Sun, 30 Sep 2018 23:21:37 +0800</pubDate><description><![CDATA[哇擦，本硕工商管理的博士生学长竟然能整理分享出如此完整的python学习框架。分享与整理才是掌握一门技能的王道啊，王道啊
分享和整理能推进你去实践

用自己的话去阐述内容
改写到自己的目录中去


-实践它，多使用便捷的工具


创新是在它人的基础上


 每天的内容做整理
  补充或优化之前的笔记、项目
重复即记忆

复用即记忆

分享即记忆









论文
工作




应用
项目

...]]></description><category></category></item><item><title><![CDATA[17个新手常见Python运行时错误]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/80469516</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/80469516</guid><author>acoco_wang</author><pubDate>Sun, 27 May 2018 15:09:11 +0800</pubDate><description><![CDATA[https://www.oschina.net/question/89964_62779]]></description><category></category></item><item><title><![CDATA[pandas]]></title><link>https://blog.youkuaiyun.com/acoco_wang/article/details/80310430</link><guid>https://blog.youkuaiyun.com/acoco_wang/article/details/80310430</guid><author>acoco_wang</author><pubDate>Mon, 14 May 2018 15:39:33 +0800</pubDate><description><![CDATA[
文档 http://pandas.pydata.org/pandas-docs/stable/api.html#id9
df.to_csv ( mode=’a’,header=False)
df=pd.concat([df1,df2],ignore_index=True,…)
]]></description><category></category></item></channel></rss>