<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[Working. Playing.]]></title><description><![CDATA[Too much to learn. Too much to enjoy.]]></description><link>https://blog.youkuaiyun.com/menc15</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; menc15]]></copyright><item><title><![CDATA[python快排：一个pythonic的写法]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/78997704</link><guid>https://blog.youkuaiyun.com/menc15/article/details/78997704</guid><author>menc15</author><pubDate>Sun, 07 Jan 2018 21:20:00 +0800</pubDate><description><![CDATA[来自 http://cs231n.github.io/python-numpy-tutorial/

def quicksort(arr):
    if len(arr) 1:
        return arr
    pivot = arr[len(arr) // 2]
    left = [x for x in arr if x < pivot]
    middle = [x for]]></description><category></category></item><item><title><![CDATA[Stanford CS231n 学习笔记：Lecture 1 Introduction]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/78995963</link><guid>https://blog.youkuaiyun.com/menc15/article/details/78995963</guid><author>menc15</author><pubDate>Sun, 07 Jan 2018 17:23:03 +0800</pubDate><description><![CDATA[第一讲 绪论 [讲义][视频]

这一讲主要介绍了CV的研究历史。我觉得以下知识比较有价值：


有研究者认为，在5.4亿年前的物种大爆炸是由视觉的产生导致的
视觉领域的研究问题有哪几个
从2000年开始的几个关键性工作


Lecture 2 听到一半忽然觉得还是要写笔记的，先列个大纲在这，等我听完再来补充……]]></description><category></category></item><item><title><![CDATA[Ubuntu "Unable to locate package lrzsz"解决办法]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/78797996</link><guid>https://blog.youkuaiyun.com/menc15/article/details/78797996</guid><author>menc15</author><pubDate>Wed, 13 Dec 2017 23:18:09 +0800</pubDate><description><![CDATA[在Ubuntu上使用以下命令安装lrzsz时报错：$ sudo apt-get install lrzsz
Reading package lists... Done
Building dependency tree       
Reading state information... Done
E: Unable to locate package lrzsz百度之，普遍说法是输入以下两条命令$]]></description><category></category></item><item><title><![CDATA[RNN的神奇之处（The Unreasonable Effectiveness of Recurrent Neural Networks）]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/78775010</link><guid>https://blog.youkuaiyun.com/menc15/article/details/78775010</guid><author>menc15</author><pubDate>Mon, 11 Dec 2017 18:54:21 +0800</pubDate><description><![CDATA[本文译自http://karpathy.github.io/2015/05/21/rnn-effectiveness/。]]></description><category></category></item><item><title><![CDATA[C++知识积累]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/77182939</link><guid>https://blog.youkuaiyun.com/menc15/article/details/77182939</guid><author>menc15</author><pubDate>Tue, 15 Aug 2017 10:01:09 +0800</pubDate><description><![CDATA[本文主要记录C++中不太熟悉的基础语法知识。 
参考：http://www.runoob.com/cplusplus/cpp-tutorial.html]]></description><category></category></item><item><title><![CDATA[常用Vim命令及快捷键]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/76165288</link><guid>https://blog.youkuaiyun.com/menc15/article/details/76165288</guid><author>menc15</author><pubDate>Wed, 26 Jul 2017 20:41:30 +0800</pubDate><description><![CDATA[常用vim命令]]></description><category></category></item><item><title><![CDATA[Logistic Regression是凸优化问题吗？]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/72231939</link><guid>https://blog.youkuaiyun.com/menc15/article/details/72231939</guid><author>menc15</author><pubDate>Mon, 15 May 2017 23:16:37 +0800</pubDate><description><![CDATA[对LR的理论探讨]]></description><category></category></item><item><title><![CDATA[Linux/Windows/Mac OS中的回车与换行]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/71731825</link><guid>https://blog.youkuaiyun.com/menc15/article/details/71731825</guid><author>menc15</author><pubDate>Fri, 12 May 2017 15:16:35 +0800</pubDate><description><![CDATA[不同操作系统下的”回车”（carriage return）和”换行”（line feed），原文：http://www.ruanyifeng.com/blog/2006/04/post_213.html]]></description><category></category></item><item><title><![CDATA[深度学习中的batch、batch size与epoch]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/71628019</link><guid>https://blog.youkuaiyun.com/menc15/article/details/71628019</guid><author>menc15</author><pubDate>Thu, 11 May 2017 14:07:43 +0800</pubDate><description><![CDATA[batch: batch是批。我们可以把数据全扔进去当作一批（Full Batch Learning), 也可以把数据分为好几批，分别扔进去Learning Model。]]></description><category></category></item><item><title><![CDATA[Conda常用命令整理]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/71477949</link><guid>https://blog.youkuaiyun.com/menc15/article/details/71477949</guid><author>menc15</author><pubDate>Tue, 09 May 2017 15:29:15 +0800</pubDate><description><![CDATA[对Conda常用命令的整理，主要参考Anaconda官方指南Using Conda：https://conda.io/docs/using/index.html]]></description><category></category></item><item><title><![CDATA[深入理解LSTM神经网络]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/71271566</link><guid>https://blog.youkuaiyun.com/menc15/article/details/71271566</guid><author>menc15</author><pubDate>Sat, 06 May 2017 16:35:54 +0800</pubDate><description><![CDATA[LSTM核心思想及详细解读]]></description><category></category></item><item><title><![CDATA[python 含中文的json格式文件输出]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/70992418</link><guid>https://blog.youkuaiyun.com/menc15/article/details/70992418</guid><author>menc15</author><pubDate>Sun, 30 Apr 2017 09:42:20 +0800</pubDate><description><![CDATA[json.dumps在默认情况下，对于非ascii字符生成的是相对应的字符编码，而非原始字符，例如：     import json
     js = json.loads('{"haha": "哈哈"}')
     print json.dumps(js)以上代码的输出结果为： 
{“haha”: “\u54c8\u54c8”}解决办法很简单: 
python 
 print json.dum]]></description><category></category></item><item><title><![CDATA[Win10 XGBoost的安装]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/66975321</link><guid>https://blog.youkuaiyun.com/menc15/article/details/66975321</guid><author>menc15</author><pubDate>Mon, 27 Mar 2017 19:39:01 +0800</pubDate><description><![CDATA[XGBoost全称是eXtreme Gradient Boost，是Gradient Boosting Machine的一个C++实现，由Tianqi Chen设计并开发，目前已完全开源。XGBoost具有速度快、效果好、功能多的特点，获得了业界的广泛认可。本文将介绍如何在Windows平台上快速安装XGBoost及其Python接口。]]></description><category></category></item><item><title><![CDATA[Win10 64位 TensorFlow安装与使用]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/66973640</link><guid>https://blog.youkuaiyun.com/menc15/article/details/66973640</guid><author>menc15</author><pubDate>Mon, 27 Mar 2017 17:06:47 +0800</pubDate><description><![CDATA[事实证明，在电脑上同时保持不同版本Python的比较好的方式是使用各种虚拟环境来进行管理，比如TensorFlow官网指南中使用的Anaconda。]]></description><category></category></item><item><title><![CDATA[Win10 64位系统下安装Python3及pip3]]></title><link>https://blog.youkuaiyun.com/menc15/article/details/65631380</link><guid>https://blog.youkuaiyun.com/menc15/article/details/65631380</guid><author>menc15</author><pubDate>Fri, 24 Mar 2017 15:21:37 +0800</pubDate><description><![CDATA[在已有Python2的情况下安装Python3及pip3]]></description><category></category></item></channel></rss>