<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[bandaye3的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/bandaye3</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; bandaye3]]></copyright><item><title><![CDATA[DyNet 基础知识（持续更新中...）]]></title><link>https://blog.youkuaiyun.com/bandaye3/article/details/83997528</link><guid>https://blog.youkuaiyun.com/bandaye3/article/details/83997528</guid><author>bandaye3</author><pubDate>Mon, 12 Nov 2018 19:50:45 +0800</pubDate><description><![CDATA[1. ParameterCollection()
DyNet最基础的概念之一是参数集合，其定义为如下：
class dynet.ParameterCollection(parent=None)
模型所需要参数的创建、加载和保存都通过此类对象实现，是普通参数和查找表参数的容器。dy.Trainer对象认为ParameterCollection对象中的参数是需要通过训练学习得到的。
add_looku...]]></description><category></category></item><item><title><![CDATA[Tensorflow 中 RNN 的相关使用方法说明]]></title><link>https://blog.youkuaiyun.com/bandaye3/article/details/83902731</link><guid>https://blog.youkuaiyun.com/bandaye3/article/details/83902731</guid><author>bandaye3</author><pubDate>Fri, 09 Nov 2018 20:09:35 +0800</pubDate><description><![CDATA[文章目录1. basic rnn1.1 __call__ method1.2 zero_state method1.3 program examples2. basic lstm2.1 program examples3. lstm4. multi layers4.1 program example 14.2 program example 24.3 program example 35. mul...]]></description><category></category></item><item><title><![CDATA[Python defaultdict() 的理解]]></title><link>https://blog.youkuaiyun.com/bandaye3/article/details/83479771</link><guid>https://blog.youkuaiyun.com/bandaye3/article/details/83479771</guid><author>bandaye3</author><pubDate>Sun, 28 Oct 2018 23:08:03 +0800</pubDate><description><![CDATA[首先来看下具体的定义：
class collections.defaultdict([default_factory[, ...]])
'''
Returns a new dictionary-like object. defaultdict is a subclass of the built-in dict class. It overrides one method and adds one...]]></description><category></category></item><item><title><![CDATA[Python 关键字 yield 的理解]]></title><link>https://blog.youkuaiyun.com/bandaye3/article/details/83477242</link><guid>https://blog.youkuaiyun.com/bandaye3/article/details/83477242</guid><author>bandaye3</author><pubDate>Sun, 28 Oct 2018 19:28:06 +0800</pubDate><description><![CDATA[Python 关键字 yield 的理解

为了更好地理解关键字yield的用法，首先需要理解迭代器（iterator）与生成器（generator）的区别。当创建列表中的元素时，我们可以使用for循环：
&amp;amp;gt;&amp;amp;gt;&amp;amp;gt; myIterator = [x*x for x in range(3)]
&amp;amp;gt;&amp;amp;gt;&amp;amp;gt; print(myIterator)
[0, 1, 4]

因此我们称...]]></description><category></category></item><item><title><![CDATA[项目三：爬取视频磁力链接]]></title><link>https://blog.youkuaiyun.com/bandaye3/article/details/77574372</link><guid>https://blog.youkuaiyun.com/bandaye3/article/details/77574372</guid><author>bandaye3</author><pubDate>Fri, 25 Aug 2017 15:10:21 +0800</pubDate><description><![CDATA[项目三：爬取视频磁力链接标签（空格分隔）： 爬虫 BeautifulSoup—具体技术实现原理类似项目四1. 项目任务分析类似上一个小项目中爬取图片的技术原理，本次小项目尝试对相同网站上的可供下载视频的磁力链接进行爬取2. 项目功能分析2.1 爬取视频列表网页上视频信息如上图所示，所以要先定义一个模块来获取如图所示的视频列表信息，查看网页源代码如下图所示 
 
显然每一个视频名称保存在a.strin]]></description><category></category></item><item><title><![CDATA[项目二：爬取网页图片]]></title><link>https://blog.youkuaiyun.com/bandaye3/article/details/74079771</link><guid>https://blog.youkuaiyun.com/bandaye3/article/details/74079771</guid><author>bandaye3</author><pubDate>Sat, 01 Jul 2017 20:36:52 +0800</pubDate><description><![CDATA[项目四：爬取网页图片标签（空格分隔）： 爬虫1. 项目需求分析要爬取图片所在网页url = 'http://www.99rblc.com/ozgq/6/i.htm'1.1 查找相应标签得到图片所在链接及其名字后，跳转新的图片所在链接，并按照图片名字建立相应文件夹1.2 跳转至新的链接，查找标签得到该图片文件所在的链接，爬取下来存入建立的文件夹中1.3 重复上述步骤遍历所有图片2. 项目功能分析2.1]]></description><category></category></item><item><title><![CDATA[项目一：股票信息定向爬虫]]></title><link>https://blog.youkuaiyun.com/bandaye3/article/details/74079767</link><guid>https://blog.youkuaiyun.com/bandaye3/article/details/74079767</guid><author>bandaye3</author><pubDate>Sat, 01 Jul 2017 20:34:46 +0800</pubDate><description><![CDATA[项目三：股票信息定向爬虫标签（空格分隔）： 爬虫—BIT Python网络爬虫与信息提取 实例三1.getStockList()函数分析a = soup.find_all('a')
    for i in a:
        try:
            href = i.attrs['href']
            lst.append(re.findall(r"[s][hz]\d{]]></description><category></category></item></channel></rss>