<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[bailian的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/YoungChiu2016</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; YoungChiu2016]]></copyright><item><title><![CDATA[【matplotlib字体问题】‘SimHei‘ is not a valid value for style； supported values are ‘normal‘, ‘ita]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/134650701</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/134650701</guid><author>YoungChiu2016</author><pubDate>Mon, 27 Nov 2023 17:43:58 +0800</pubDate><description><![CDATA[【代码】【matplotlib字体问题】'SimHei' is not a valid value for style;]]></description><category></category></item><item><title><![CDATA[django 数据迁移makemigrations和migrate的备忘录]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/130721374</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/130721374</guid><author>YoungChiu2016</author><pubDate>Wed, 17 May 2023 11:37:58 +0800</pubDate><description><![CDATA[不然启动项目，会报错：no module named MySQLdb。两条命令最好记得，如果通过pycharm， 会自动生成一个。pycharm创建django会自动添加。后，数据库没有生成对应的数据表；本来不是大问题，细心点就好了。目录，而这两条命令，正是一个。之前成功生成过，重新执行。]]></description><category></category></item><item><title><![CDATA[数学基础之概率论1]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126456234</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126456234</guid><author>YoungChiu2016</author><pubDate>Sun, 21 Aug 2022 22:04:29 +0800</pubDate><description><![CDATA[概率论1]]></description><category></category></item><item><title><![CDATA[数学基础之最大似然准则]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126454311</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126454311</guid><author>YoungChiu2016</author><pubDate>Sun, 21 Aug 2022 20:32:01 +0800</pubDate><description><![CDATA[最大似然原则]]></description><category></category></item><item><title><![CDATA[数学基础之曲线拟合]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126453793</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126453793</guid><author>YoungChiu2016</author><pubDate>Sun, 21 Aug 2022 19:23:54 +0800</pubDate><description><![CDATA[曲线拟合]]></description><category></category></item><item><title><![CDATA[循环神经网络基础]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126331861</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126331861</guid><author>YoungChiu2016</author><pubDate>Sun, 14 Aug 2022 19:59:45 +0800</pubDate><description><![CDATA[循环网络]]></description><category></category></item><item><title><![CDATA[卷积网络之池化]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126331478</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126331478</guid><author>YoungChiu2016</author><pubDate>Sun, 14 Aug 2022 15:05:16 +0800</pubDate><description><![CDATA[池化]]></description><category></category></item><item><title><![CDATA[深度学习卷积网络之卷积运算]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126330289</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126330289</guid><author>YoungChiu2016</author><pubDate>Sun, 14 Aug 2022 12:17:45 +0800</pubDate><description><![CDATA[卷积运算]]></description><category></category></item><item><title><![CDATA[深度学习简介]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126213528</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126213528</guid><author>YoungChiu2016</author><pubDate>Sun, 07 Aug 2022 16:54:02 +0800</pubDate><description><![CDATA[深度学习简介]]></description><category></category></item><item><title><![CDATA[深度学习数学基础之激活函数与导数]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126211189</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126211189</guid><author>YoungChiu2016</author><pubDate>Sun, 07 Aug 2022 16:04:54 +0800</pubDate><description><![CDATA[​​激活函数与sigmoid函数的导数]]></description><category></category></item><item><title><![CDATA[深度学习数学基础之张量与范数]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126211118</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/126211118</guid><author>YoungChiu2016</author><pubDate>Sun, 07 Aug 2022 14:48:54 +0800</pubDate><description><![CDATA[深度学习之数学基础  标量、向量、矩阵与张量]]></description><category></category></item><item><title><![CDATA[解决安装时间序列分析库fbprophet]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/125917597</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/125917597</guid><author>YoungChiu2016</author><pubDate>Thu, 21 Jul 2022 18:14:13 +0800</pubDate><description><![CDATA[安装fbprophet]]></description><category></category></item><item><title><![CDATA[蓝桥杯基础题]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/121766957</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/121766957</guid><author>YoungChiu2016</author><pubDate>Tue, 07 Dec 2021 13:25:30 +0800</pubDate><description><![CDATA[猜年龄
美国数学家维纳11岁上大学，曾在1935-1936年应邀来清华讲学。一次 ，他参加某个会议，年轻的脸孔引人注目，于是有人询问他年龄，他回答：“我的年龄的立方是个4位数，4次方是6位数。这10个数字正好包含了从0到9这10个数字。”
def guess_age():
    import math
    rec=set()
    low=math.ceil(math.pow(10**5,1/4))
    high=math.floor(math.pow(9999,1/3))
    for i ]]></description><category></category></item><item><title><![CDATA[2021-10-20 python安装第三方库，报错Failed to build]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/120871072</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/120871072</guid><author>YoungChiu2016</author><pubDate>Wed, 20 Oct 2021 18:15:49 +0800</pubDate><description><![CDATA[python安装第三方库，报错Failed to build prophet
系统：WIN10
软件：Anaconda Prompt
起因与问题
执行
pip install prophet

或
python -m pip install prophet

安装失败,报错有点长，
Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple
Collecting prophet
  Using cached https://pypi.tuna.t]]></description><category></category></item><item><title><![CDATA[python的pip 镜像使用帮助]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/108733107</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/108733107</guid><author>YoungChiu2016</author><pubDate>Tue, 22 Sep 2020 15:21:53 +0800</pubDate><description><![CDATA[pypi 镜像使用帮助
pypi 镜像每 5 分钟同步一次。
临时使用
常见的镜像
https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple/
https://pypi.tuna.tsinghua.edu.cn/simple   
http://mirrors.aliyun.com/pypi/simple/
http://mirrors.tencentyun.com/pypi/simple 不可用
https://pypi.doubanio.com/simpl]]></description><category></category></item><item><title><![CDATA[使用neurolab报错AssertionError]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/107636426</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/107636426</guid><author>YoungChiu2016</author><pubDate>Tue, 28 Jul 2020 15:43:27 +0800</pubDate><description><![CDATA[运行下句报错AssertionError


err=net.train(train_x,train_y,epochs=100, show=1, goal=0.02)

如图所示



突然发现根本不懂“net.ci“是什么，在notebook里输入net.ci，得到13；而input就是train_x训练集，train_x.shape就是训练集的行列，是36，难怪出错。往上找，发现net.ci可能是nl.net.newff中的maxmin的长度，可能是计算max与min时出问题了。

修改了maxmin，]]></description><category></category></item><item><title><![CDATA[学习笔记(04):21天通关Python（仅视频课）-序列与列表与元组的关系和创建]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/106087202</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/106087202</guid><author>YoungChiu2016</author><pubDate>Tue, 12 May 2020 22:50:17 +0800</pubDate><description><![CDATA[本页面购买不发书！！！仅为视频课购买！！！ 


	请务必到https://edu.youkuaiyun.com/bundled/detail/49下单购买课+书。 


	本页面，仅为观看视频页面，如需一并购买图书，请务必到https://edu.youkuaiyun.com/bundled/detail/49下单购买课程+图书！！！ 


	


	疯狂Python精讲课程覆盖《疯狂Py...]]></description><category></category></item><item><title><![CDATA[数据分析准备阶段遇到的若干问题]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/105702432</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/105702432</guid><author>YoungChiu2016</author><pubDate>Thu, 23 Apr 2020 11:02:40 +0800</pubDate><description><![CDATA[1、将两个一维数组转换成二维数组。如将DataFrame的某字段作为其中一个数组，另一个数组的元素都为零，如下：


X=np.array(list(zip(np.array(df['user_count']),np.zeros(shape=(500000,)))))



2、

未完待续。。。
...]]></description><category></category></item><item><title><![CDATA[学习笔记(03):Python数据清洗实战-异常值处理]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/104963084</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/104963084</guid><author>YoungChiu2016</author><pubDate>Thu, 19 Mar 2020 11:11:39 +0800</pubDate><description><![CDATA[本次课程主要以真实的电商数据为基础，通过Python详细的介绍了数据分析中的数据清洗阶段各种技巧和方法。
]]></description><category></category></item><item><title><![CDATA[学习笔记(01):Python数据清洗实战-聚合函数使用]]></title><link>https://blog.youkuaiyun.com/YoungChiu2016/article/details/104934626</link><guid>https://blog.youkuaiyun.com/YoungChiu2016/article/details/104934626</guid><author>YoungChiu2016</author><pubDate>Tue, 17 Mar 2020 23:37:22 +0800</pubDate><description><![CDATA[本次课程主要以真实的电商数据为基础，通过Python详细的介绍了数据分析中的数据清洗阶段各种技巧和方法。
]]></description><category></category></item></channel></rss>