<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[张启宇(Joey Zhang)的专栏]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/yu444</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; yu444]]></copyright><item><title><![CDATA[Spring Introduction -1]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/89070325</link><guid>https://blog.youkuaiyun.com/yu444/article/details/89070325</guid><author>yu444</author><pubDate>Sun, 07 Apr 2019 16:53:34 +0800</pubDate><description><![CDATA[Spring SummarySpring BootSpring Boot 2.0Installation of Spring BootDeveloping Your First Spring Boot Application
Spring Boot
Spring Boot is designed to get you up and running as quickly as possible, w...]]></description><category></category></item><item><title><![CDATA[LSTM模型介绍]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86764352</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86764352</guid><author>yu444</author><pubDate>Mon, 04 Feb 2019 23:31:54 +0800</pubDate><description><![CDATA[递归神经网络（RNN）
人类不会每时每刻都开始思考。 当你阅读这篇文章时，你会根据你对之前单词的理解来理解每个单词。 你不会忘掉掉所有东西，然后再从头开始思考。 你的想法有持久性。
传统的神经网络不能做到这一点，这是一个主要的缺点。 例如，假设您想要对电影视频中每个点发生的事件进行分类。 目前尚传统神经网络无法利用其对电影中先前事件的推理来预测后者。
循环神经网络解决了这个问题。 它们是带有循环的...]]></description><category></category></item><item><title><![CDATA[Keras：Python深度学习库简介]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86657903</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86657903</guid><author>yu444</author><pubDate>Sat, 26 Jan 2019 16:24:01 +0800</pubDate><description><![CDATA[Keras：Python深度学习库简介

Keras是一个高级神经网络API，用Python编写，能够在TensorFlow，CNTK或Theano之上运行。 它的开发重点是实现快速开发。 能够以最小的时间成本从理论到结果，这也进行快速研究验证的关键。
如果您需要深度学习库，请使用Keras：

允许简单快速的原型设计（通过用户友好接口，模块化和可扩展性）。
支持卷积网络和循环网络，以及两者的组合...]]></description><category></category></item><item><title><![CDATA[Keras: The Python Deep Learning library Introduction]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86657281</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86657281</guid><author>yu444</author><pubDate>Sat, 26 Jan 2019 15:32:59 +0800</pubDate><description><![CDATA[Keras: The Python Deep Learning library Introduction

Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a...]]></description><category></category></item><item><title><![CDATA[在Kaggle的使用新闻预测股票涨跌的AI 建模竞赛(2-Sigma 赞助)]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86653601</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86653601</guid><author>yu444</author><pubDate>Sat, 26 Jan 2019 00:48:45 +0800</pubDate><description><![CDATA[在Kaggle的使用新闻预测股票涨跌的AI建模竞赛(2-Sigma 赞助)
我们可以使用新闻分析的内容来预测股价表现吗？ 如今无处不在的数据使投资者能够以任何规模做出更好的投资决策。 这个竞赛在于提取和解释数据以确定哪些数据有用，在这个信息海洋中找到信号。 Two Sigma对这一挑战充满热情，并很高兴与Kaggle社区分享。
这场比赛最让人兴奋的是，Kaggle现在正在使用提交的模型进行实时的未...]]></description><category></category></item><item><title><![CDATA[The introduction of Two Sigma(Using News to Predict Stock Movements) AI competition at Kaggle]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86653023</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86653023</guid><author>yu444</author><pubDate>Sat, 26 Jan 2019 00:04:25 +0800</pubDate><description><![CDATA[The introduction of Two Sigma(Using News to Predict Stock Movements) competition at Kaggle

]]></description><category></category></item><item><title><![CDATA[Python 3.7.x 介绍-8 标准库 2]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86620331</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86620331</guid><author>yu444</author><pubDate>Thu, 24 Jan 2019 09:44:09 +0800</pubDate><description><![CDATA[Python 3.7.x 介绍-8 标准库 2
输出格式化
reprlib模块提供了一个版本的repr（），用于大型或深层嵌套容器的缩写显示：
&amp;gt;&amp;gt;&amp;gt; import reprlib
&amp;gt;&amp;gt;&amp;gt; reprlib.repr(set('supercalifragilisticexpialidocious'))
&quot;{'a', 'c', 'd', 'e', 'f', 'g',...]]></description><category></category></item><item><title><![CDATA[Python 3.7.x Notes-8 Standard Library 2]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86620107</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86620107</guid><author>yu444</author><pubDate>Thu, 24 Jan 2019 09:03:35 +0800</pubDate><description><![CDATA[Python 3.7.x Notes-8 Standard Library 2
Output Formatting
The reprlib module provides a version of repr() customized for abbreviated displays of large or deeply nested containers:
&amp;gt;&amp;gt;&amp;gt; import ...]]></description><category></category></item><item><title><![CDATA[Python 3.7.x 介绍-7 标准库]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86603938</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86603938</guid><author>yu444</author><pubDate>Wed, 23 Jan 2019 08:02:37 +0800</pubDate><description><![CDATA[标准库介绍
操作系统接口
&amp;amp;gt;&amp;amp;gt;&amp;amp;gt; import os
&amp;amp;gt;&amp;amp;gt;&amp;amp;gt; os.getcwd()      # Return the current working directory
'C:\\Python37'
&amp;amp;gt;&amp;amp;gt;&amp;amp;gt; os.chdir('/server/accesslogs')   # Change curr]]></description><category></category></item><item><title><![CDATA[Python 3.7.x Notes-7 Standard Library]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86603927</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86603927</guid><author>yu444</author><pubDate>Wed, 23 Jan 2019 07:47:47 +0800</pubDate><description><![CDATA[Brief Tour of the Standard Library
Operating System Interface
&amp;amp;gt;&amp;amp;gt;&amp;amp;gt; import os
&amp;amp;gt;&amp;amp;gt;&amp;amp;gt; os.getcwd()      # Return the current working directory
'C:\\Python37'
&amp;amp;gt;&amp;amp;gt;&amp;amp;g]]></description><category></category></item><item><title><![CDATA[TensorFlow development environment setup with Anaconda (windows)]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86586225</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86586225</guid><author>yu444</author><pubDate>Tue, 22 Jan 2019 00:21:18 +0800</pubDate><description><![CDATA[TensorFlow is an open-source software library for dataflow programming across a range of tasks. It is a symbolic math library, and is also used for machine learning applications such as neural network...]]></description><category></category></item><item><title><![CDATA[使用Anaconda设置TensorFlow开发环境（windows）]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86587184</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86587184</guid><author>yu444</author><pubDate>Tue, 22 Jan 2019 00:20:35 +0800</pubDate><description><![CDATA[TensorFlow是一个开源软件库，用于跨越一系列任务进行数据流编程。 它是一个符号数学库，也用于机器学习应用程序，如神经网络。 它用于Google的AI研究和开发。
它被世界级企业广泛使用，是个人开发者探索这一领域的最佳开源库。
开源Anaconda Distribution是在Linux，Windows和Mac OS X上进行Python和R数据科学和机器学习的最快和最简单的方法。它是在单个...]]></description><category></category></item><item><title><![CDATA[使用TensorFlow进行股票价格预测的简单深度学习模型]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86563786</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86563786</guid><author>yu444</author><pubDate>Sun, 20 Jan 2019 19:00:56 +0800</pubDate><description><![CDATA[使用TensorFlow进行股票价格预测的简单深度学习模型（翻译）
原文链接：https://medium.com/mlreview/a-simple-deep-learning-model-for-stock-price-prediction-using-tensorflow-30505541d877
深度学习在金融市场的应用越来越广泛，这篇来自作者 Sebastian Heinz 的好文起到了...]]></description><category></category></item><item><title><![CDATA[Python 3.7.x 介绍-6类]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86557898</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86557898</guid><author>yu444</author><pubDate>Sun, 20 Jan 2019 00:06:07 +0800</pubDate><description><![CDATA[类
类提供了将数据和功能捆绑在一起的方法。 创建新类会创建一种新类型的对象，从而允许创建该类型的新实例。 每个类实例都可以附加属性以保持其状态。 类实例还可以具有用于修改其状态的方法（由其类定义）。 与其他编程语言相比，Python的类机制添加了具有最少新语法和语义的类。 它是C ++和Modula-3中的类机制的混合体。 Python类提供面向对象编程的所有标准功能与C ++和Modula-3不...]]></description><category></category></item><item><title><![CDATA[Python 3.7.x Notes-6 Classes]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86555601</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86555601</guid><author>yu444</author><pubDate>Sat, 19 Jan 2019 22:28:43 +0800</pubDate><description><![CDATA[Classes
Classes provide a means of bundling data and functionality together. Creating a new class creates a new type of object, allowing new instances of that type to be made. Each class instance can ...]]></description><category></category></item><item><title><![CDATA[Python 3.7.x 介绍-5 错误和异常处理]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86552929</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86552929</guid><author>yu444</author><pubDate>Sat, 19 Jan 2019 15:54:44 +0800</pubDate><description><![CDATA[错误和异常处理
语法错误
语法错误（也称为解析错误）可能是您在学习Python时最常见的问题：
&amp;amp;gt;&amp;amp;gt;&amp;amp;gt; while True print('Hello world')
  File &amp;quot;&amp;amp;lt;stdin&amp;amp;gt;&amp;quot;, line 1
    while True print('Hello world')
                   ^
SyntaxErro]]></description><category></category></item><item><title><![CDATA[Python 3.7.x Notes-5 Errors and Exceptions]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86552475</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86552475</guid><author>yu444</author><pubDate>Sat, 19 Jan 2019 15:24:02 +0800</pubDate><description><![CDATA[Errors and Exceptions
Syntax Errors
Syntax errors, also known as parsing errors, are perhaps the most common kind of complaint you get while you are still learning Python:
&amp;amp;gt;&amp;amp;gt;&amp;amp;gt; while True prin...]]></description><category></category></item><item><title><![CDATA[Python 3.7.x 介绍-1概述]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86550814</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86550814</guid><author>yu444</author><pubDate>Sat, 19 Jan 2019 12:00:35 +0800</pubDate><description><![CDATA[1 容易学习
高效的高级数据结构
面向对象编程的简单方法
简洁的语法和动态类型
Python解释器
通过C / C ++轻松扩展
来自主要Python平台的大量源代码或二进制文件库
使用Python解释器
通常安装在c：\ python37 Python命令行示例：。
python -c命令[arg] …
python -m module [arg] …参数传递。
通过import sys访问参数...]]></description><category></category></item><item><title><![CDATA[Python 3.7.x 介绍 -4 输入和输出]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86550335</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86550335</guid><author>yu444</author><pubDate>Sat, 19 Jan 2019 11:46:03 +0800</pubDate><description><![CDATA[输入和输出
等好的输出格式控制
到目前为止，我们遇到了两种写入值的方法：表达式语句和print（）函数。 要使用格式化的字符串文字，请在开始引号或三引号之前键入一个带有f或F的字符串。
&amp;gt;&amp;gt;&amp;gt; year = 2016
&amp;gt;&amp;gt;&amp;gt; event = 'Referendum'
&amp;gt;&amp;gt;&amp;gt; f'Results of the {year} {event}'
'R...]]></description><category></category></item><item><title><![CDATA[Python 3.7.x Notes -4 Input & Output]]></title><link>https://blog.youkuaiyun.com/yu444/article/details/86549499</link><guid>https://blog.youkuaiyun.com/yu444/article/details/86549499</guid><author>yu444</author><pubDate>Sat, 19 Jan 2019 11:12:46 +0800</pubDate><description><![CDATA[Input and Output
Fancier Output Formatting
So far we’ve encountered two ways of writing values: expression statements and the print() function.
To use formatted string literals, begin a string with f ...]]></description><category></category></item></channel></rss>