Less is exponentially more  (原文出处:rob pike 博客,https://commandcenter.blogspot.jp/2012/06/less-is-exponentially-more.html ) Here is the text of the talk I gave at the Go SF meeting in June, 2012.This is a personal talk. I do not speak for anyone else o…

13年上半年接触了Golang,对Golang十分喜爱.现在是2015年,离春节还有几天,从开始学习到现在的一年半时间里,前前后后也用Golang写了些代码,其中包括业余时间的,也有产品项目中的.一直有想法写点Golang相关的总结或者感想,决定还是在年前总结下吧.注明下:我只是Golang的喜好者,不是脑残粉,也无意去挑起什么语言之争. 特性少,语法简单.GO是崇尚极简主义的,提倡少即是多.这点在它的Spec上尤其凸显,一下午的时间绝对可以看完.GO的特性很少,很多GO的使用者都反馈,GO的关…

今天,我们要讲的是angualr2的pipe这个知识点. 例子…

2008-11   Satoshi Nakamoto  Bitcoin: A Peer-to-Peer Electronic Cash System http://p2pbucks.com/?p=9963 https://bitcoin.org/bitcoin.pdf http://www.useit.com.cn/thread-11046-1-1.html 比特币白皮书,一种点对点的电子现金系统 1. 比特币白皮书简介 互联网上的贸易,几乎都需要借助金融机构作为可资信赖的第三方来处理电子支付信…

Android Lint Checks Here are the current list of checks that lint performs as of Android Studio 2.3 dev:     Correctness ===========   AdapterViewChildren ------------------- Summary: AdapterViews cannot have children in XML   Priority: 10 / 10 Sever…

http://www.ithao123.cn/content-296918.html 首页 > 技术 > 编程 > Python > Python 文本挖掘:简单的自然语言统计 Python 文本挖掘:简单的自然语言统计 2015-05-12 浏览(141)   [摘要:首要应用NLTK (Natural Language Toolkit)顺序包. 实在,之前正在用呆板进修方式剖析情绪的时间便已应用了简略的天然说话处置惩罚及统计.比方把分词后的文本变成单词拆配(或叫单词序] 主要使…

TCP连接中,最重要的是连接TCP连接上,两个方向之间的各个状态及各个系统调用与状态之间的关系.往往可以以两种图表示,第一种是状态转换图,第二种是连接时序图.如下: 状态图: 时序图:         可见,listen状态是服务器接收连接建立的必经之路.调用listen后,服务器即进入了LISTEN状态. listen为: int listen(int sockfd, int backlog); 其backlog是一个建议值,用于指定内部的队列大小,以控制同时建立的连接请求数量.   针对控制…

1 Canvas教程 <canvas>是一个新的用于通过脚本(通常是JavaScript)绘图的HTML元素.例如,他可以用于绘图.制作图片的组合或者简单的动画(当然并不那么简单).It can for instance be used to draw graphs, make photo compositions or do simple (and not so simple) animations. 1.1 基本用法 Basic usage <canvas>元素 Let's s…

Let $X=\{x_1,x_2,...,x_n\}$ be a finite set and let $P$ be a probability function defined on all subsets of $X$ with $P(\{x_i\})=a_i,~1\leq i \geq n,~0<a_i<1$ for i and $\sum^{n}_{i=1}=1$. $X$ together with $P$ is a discrete (finite) probability dis…

若干年后,经验有一些,但根基不牢靠.[algorithm] series 借助学习Standard Template Library: Algorithms的这段时期,在自己的算法和c++基础方面加些钢筋和混凝土,也为上层建筑提供有力的支持. 愿那些自称ITer但编程不过关的人……原地自爆yo. 证明的重要性: Proofs are NOT academic embellishments - sometimes they are the only way to know that our alg…

What is Configuration Management? Configuration Management refers to the process by which all artifacts relevant to your project, and the relationships between them, are stored, retrieved, uniquely identified and modified. As a good configuration man…

来源:http://deeplearning.net/software/theano/tutorial/index.html#tutorial 这里介绍的是使用theano的一些基础知识,虽然theano是用来dl 的,不过其中的一些函数还是挺有用的,可以用在ml 里面. 在python或者ipython的交互模式下,可以按照如下形式来import theano: >>> from theano import * 这里有几个你需要使用的符号都在theano的tensor这个子包中.让我们…

PDF version PDF & CDF The exponential probability density function (PDF) is $$f(x; \lambda) = \begin{cases}\lambda e^{-\lambda x} & x\geq0\\ 0 & x < 0 \end{cases}$$ The exponential cumulative distribution function (CDF) is $$F(x; \lambda) =…

下载本文PDF格式(Academia.edu) 本文给出了机器学习中AdaBoost算法的一个简单初等证明,需要使用的数学工具为微积分-1. Adaboost is a powerful algorithm for predicting models. However, a major disadvantage is that Adaboost may lead to over-fit in the presence of noise. Freund, Y. & Schapire, R. E.…

转载 - Recurrent Neural Networks Tutorial, Part 3 – Backpropagation Through Time and Vanishing Gradients 本文是 RNN入门教程 的第三部分. In the previous part of the tutorial we implemented a RNN from scratch, but didn’t go into detail on how Backpropagation Through…

N-Gram是大词汇连续语音识别中常用的一种语言模型,对中文而言,我们称之为汉语语言模型(CLM, Chinese Language Model).   中文名 汉语语言模型 外文名 N-Gram 定    义 计算出具有最大概率的句子 基    于 该模型基于这样一种假设 汉语语言模型利用上下文中相邻词间的搭配信息,在需要把连续无空格的拼 音.笔划,或代表字母或笔划的数字,转换成汉字串(即句子)时,可以计算出具有最大概率的句子,从而实现到汉字的自动转换,无需用户手动选择,避开了许多 汉字对应一…

引用自:http://rusanu.com/2013/08/01/understanding-how-sql-server-executes-a-query/ Understanding how SQL Server executes a query August 1st, 2013 If you are a developer writing applications that use SQL Server and you are wondering what exactly happens…

第四部分     推理题 1.世界上每个角落的每个人都有立场,都有背景,都有推理性,能推理出一个人语言的真意,才成就了真正的推理能力: 2.换言之,如果你能通过一个人的说话推理出其身份职业,你的推理能力更上一层楼. 一 . 临门一脚 1. “I believe in human ingenuity – that when we decide on a task to be done, no matter how daunting it may seem at the beginning, we…

Let's make a DQN 系列 Let's make a DQN: Theory September 27, 2016DQN This article is part of series Let's make a DQN. 1. Theory2. Implementation3. Debugging4. Full DQN5. Double DQN and Prioritized experience replay (available soon) Introduction In Febr…

<!-- metrics --> <dependency> <groupId>io.dropwizard.metrics</groupId> <artifactId>metrics-core</artifactId> </dependency> 这里,依托于springboot,版本号是3.1.2 一.meter类metrics 作用:统计最近1分钟(m1),5分钟(m5),15分钟(m15),还有全部时间的速率(速率就是…

http://www.onjava.com/pub/a/onjava/2001/05/30/optimization.htmlComparing the performance of LinkedLists and ArrayLists (and Vectors) (Page last updated May 2001, Added 2001-06-18, Author Jack Shirazi, Publisher OnJava). Tips: ArrayList is faster than…

原文地址:http://www.javacodegeeks.com/2015/07/mysql-vs-mongodb.html 1. Introduction It would be fair to say that as IT professionals we are living in the golden age of data management era. As our software systems become more complex and more distributed,…

http://scottsievert.github.io/blog/2015/01/31/the-mysterious-eigenvalue/ The Fibonacci problem is a well known mathematical problem that models population growth and was conceived in the 1200s. Leonardo of Pisa aka Fibonacci decided to use a recursiv…

Comparison of the different algorithms for  Polygon Boolean operations. Michael Leonov 1998 http://www.angusj.com/delphi/clipper.php#screenshots http://www.complex-a5.ru/polyboolean/comp.html http://www.angusj.com/delphi/clipper.php#screenshots Intro…

Deep Learning in a Nutshell: Reinforcement Learning   Share: Posted on September 8, 2016by Tim Dettmers No CommentsTagged Deep Learning, Deep Neural Networks, Machine Learning,Reinforcement Learning This post is Part 4 of the Deep Learning in a Nutsh…

An overview of gradient descent optimization algorithms Table of contents: Gradient descent variantsChallenges Batch gradient descent Stochastic gradient descent Mini-batch gradient descent Gradient descent optimization algorithms Momentum Nesterov a…

Adit Deshpande CS Undergrad at UCLA ('19) Blog About A Beginner's Guide To Understanding Convolutional Neural Networks Part 2 Introduction Link to Part 1 In this post, we’ll go into a lot more of the specifics of ConvNets. Disclaimer: Now, I do reali…

R2RT   Written Memories: Understanding, Deriving and Extending the LSTM Tue 26 July 2016 When I was first introduced to Long Short-Term Memory networks (LSTMs), it was hard to look past their complexity. I didn’t understand why they were designed the…

Andrej Karpathy blog About Hacker's guide to Neural Networks Deep Reinforcement Learning: Pong from Pixels May 31, 2016 This is a long overdue blog post on Reinforcement Learning (RL). RL is hot! You may have noticed that computers can now automatica…

本文转自:http://www.analyticsvidhya.com/blog/2016/06/quick-guide-build-recommendation-engine-python/ Introduction This could help you in building your first project! Be it a fresher or an experienced professional in data science, doing voluntary projects…