1.记录几个少见的关键字    auto 声明为自动变量,缺省时编译器一般默认为auto    register 声明寄存器变量    volatile 说明变量在程序执行中可被隐含地改变    extern 声明变量是在其他文件中声明(也可以看作是引用变量) 2.什么是定义?    所谓的定义就是(编译器)创建一个对象,为这个对象分配一块内存并给它取上一个名字,这个名字就是所说的变量名或对象名    一个变量或对象在一定的区域内(比如函数内,全局等)只能被定义一次:如果定义多次,编译器会提示用…

I’ve worked with a lot of programmers over the years — some of them super amazing, and some distinctly lackluster. As I’ve had the pleasure of working with some very skilled individuals recently, I spent some time thinking about what I admire in them…

Focus, Follow, and Forward Stanford CS224d 课程笔记 Lecture1 Stanford CS224d 课程笔记 Lecture1 Stanford大学在2015年开设了一门Deep Learning for Natural Language Processing的课程,广受好评.并在2016年春季再次开课.我将开始这门课程的学习,并做好每节课的课程笔记放在博客上.争取做到每周一更吧.本文是第一篇. NLP简介 NLP,全名Natural Languag…

Deep Learning Libraries by Language Tweet         Python Theano is a python library for defining and evaluating mathematical expressions with numerical arrays. It makes it easy to write deep learning algorithms in python. On the top of the Theano man…

Word embeding 给word 加feature,用来区分word 之间的不同,或者识别word之间的相似性. 用于学习 Embeding matrix E 的数据集非常大,比如 1B - 100B 的word corpos. 所以即使你输入的是没见过的 durian cutivator 也知道和 orange farmer 很相近. 这是transfter learning 的一个case. 因为t-SNE 做了non-liner 的转化,所以在原来的300维空间的平行的向量在转化过后…

A note on matrix implementations 将J对softmax的权重W和每一个word vector进行求导: 尽量使用矩阵运算(向量化).不要使用for loop. 模型训练中有两个开销比較大的运算:矩阵乘法f=Wx和指数函数exp Softmax(=logistic regression) is not very powerful softmax仅仅是在原来的向量空间中给出了一些linear decision boundary(线性决策线),在小的数据集上有非常好的r…

1        struct 的巨大作用 面对一个人的大型C/C++程序时,只看其对struct 的使用情况我们就可以对其编写者的编程经验进行评估.因为一个大型的C/C++程序,势必要涉及一些(甚至大量)进行数据组合的结构体,这些结构体可以将原本意义属于一个整体的数据组合在一起.从某种程度上来说,会不会用struct,怎样用struct 是区别一个开发人员是否具备丰富开发经历的标志. 在网络协议.通信控制.嵌入式系统的C/C++编程中,我们经常要传送的不是简单的字节流(char型数组),而是多…

论文地址:https://128.84.21.199/abs/1703.09831 这篇论文来自于百度的机器学习研究院,作者为:徐伟.余昊男.张海超 这篇论文用了多种技术的组合: reinforcement learning, word embedding, attention, question and answer, bidirection RNN等.模型挺复杂的,但看下面这张图能够大致弄明白.要是还能加上去年VIN(NIPS2016 best paper: Value Iteration…

边缘智能:按需深度学习模型和设备边缘协同的共同推理 本文为SIGCOMM 2018 Workshop (Mobile Edge Communications, MECOMM)论文. 笔者翻译了该论文.由于时间仓促,且笔者英文能力有限,错误之处在所难免:欢迎读者批评指正. 本文及翻译版本仅用于学习使用.如果有任何不当,请联系笔者删除. 本文作者包含3位,En Li, Zhi Zhou, and Xu Chen@School of Data and Computer Science, Sun Yat…

26 THINGS I LEARNED IN THE DEEP LEARNING SUMMER SCHOOL In the beginning of August I got the chance to attend the Deep Learning Summer School in Montreal. It consisted of 10 days of talks from some of the most well-known neural network researchers. Du…

最近在学深度学习相关的东西,在网上搜集到了一些不错的资料,现在汇总一下: Free Online Books  by Yoshua Bengio, Ian Goodfellow and Aaron Courville Neural Networks and Deep Learning42 by Michael Nielsen Deep Learning27 by Microsoft Research Deep Learning Tutorial23 by LISA lab, University…

The major advancements in Deep Learning in 2016 地址:https://tryolabs.com/blog/2016/12/06/major-advancements-deep-learning-2016/ 主要挑战是unsupervised learning 无监督学习,2016年大量的研究专注于generative models 生成模型.几大巨头谷歌和脸书分别创新于自然语言处理NLP. 无监督学习 无监督学习指的是在没有额外信息的新数据中,提取…

People are much happier moving up the ladder,socially or even technically.So our profession has moved from machine code to C/Win32 API,to C++/MFC,to java/AWT(Abstract Window Toolkit,classes for building graphics user interface in Java)/JFC(Java Found…

转自:http://www.jeremydjacksonphd.com/category/deep-learning/ Deep Learning Resources Posted on May 13, 2015   Videos Deep Learning and Neural Networks with Kevin Duh: course page NY Course by Yann LeCun: 2014 version, 2015 version NIPS 2015 Deep Learn…

转自:https://github.com/terryum/awesome-deep-learning-papers Awesome - Most Cited Deep Learning Papers A curated list of the most cited deep learning papers (since 2010) I believe that there exist classic deep learning papers which are worth reading re…

Awesome Deep Learning  Table of Contents Free Online Books Courses Videos and Lectures Papers Tutorials Researchers WebSites Datasets Frameworks Miscellaneous Contributing Free Online Books Deep Learning by Yoshua Bengio, Ian Goodfellow and Aaron Cou…

The major advancements in Deep Learning in 2016 Pablo Tue, Dec 6, 2016 in MACHINE LEARNING DEEP LEARNING GAN Deep Learning has been the core topic in the Machine Learning community the last couple of years and 2016 was not the exception. In this arti…

Deep Reinforcement Learning Papers A list of recent papers regarding deep reinforcement learning. The papers are organized based on manually-defined bookmarks. They are sorted by time to see the recent papers first. Any suggestions and pull requests…

头脑一热,坐几十个小时的硬座北上去天津大学去听了门4天的深度学习课程,课程预先的计划内容见:http://cs.tju.edu.cn/web/courseIntro.html.上课老师为微软研究院的大牛——邓力,群(qq群介绍见:Deep learning高质量交流群)里面有人戏称邓力(拼音简称DL)老师是天生注定能够在DL(Deep learning)领域有所成就的,它的个人主页见:http://research.microsoft.com/en-us/people/deng/.这次我花费这么…

By brant-ruan Yeah, I feel very happy When you want to give up, think why you have held on so long. Just fight. Somebody may ask you: Why would you want to do that? Yeah, because I want to know how it works. Assembly language programming is about mem…

从13年11月初开始接触DL,奈何boss忙or 各种问题,对DL理解没有CSDN大神 比如 zouxy09等 深刻,主要是自己觉得没啥进展,感觉荒废时日(丢脸啊,这么久....)开始开文,即为记录自己是怎么一步一个逗比的走过的路的,也为了自己思维更有条理.请看客,轻拍,(如果有错,我会立马改正,谢谢大家的指正.==!其实有人看没人看都是个问题.哈哈) 推荐 tornadomeet 的博客园学习资料 http://www.cnblogs.com/tornadomeet/category/4976…

原文转载:http://licstar.net/archives/328 Deep Learning 算法已经在图像和音频领域取得了惊人的成果,但是在 NLP 领域中尚未见到如此激动人心的结果.关于这个原因,引一条我比较赞同的微博. @王威廉:Steve Renals算了一下icassp录取文章题目中包含deep learning的数量,发现有44篇,而naacl则有0篇.有一种说法是,语言(词.句子.篇章等)属于人类认知过程中产生的高层认知抽象实体,而语音和图像属于较为底层的原始输入信号,所以…

Deep Learning in a Nutshell: History and Training This series of blog posts aims to provide an intuitive and gentle introduction to deep learning that does not rely heavily on math or theoretical constructs. The first part in this series provided an…

Top Deep Learning Projects A list of popular github projects related to deep learning (ranked by stars). Last Update: 2016.08.09 Project Name Stars Description TensorFlow 29622              Computation using data flow graphs for scalable machine lear…

HOME ABOUT CONTACT SUBSCRIBE VIA RSS   DEEP LEARNING FOR ENTERPRISE Distributed Deep Learning, Part 1: An Introduction to Distributed Training of Neural Networks Oct 3, 2016 3:00:00 AM / by Alex Black and Vyacheslav Kokorin Tweet inShare27   This pos…

Main Menu Fortune.com       E-mail Tweet Facebook Linkedin Share icons By Roger Parloff Illustration by Justin Metz SEPTEMBER 28, 2016, 5:00 PM EDT WHY DEEP LEARNING IS SUDDENLY CHANGING YOUR LIFE Decades-old discoveries are now electrifying the comp…

Adit Deshpande CS Undergrad at UCLA ('19) Blog About Resume Deep Learning Research Review Week 1: Generative Adversarial Nets Starting this week, I’ll be doing a new series called Deep Learning Research Review. Every couple weeks or so, I’ll be summa…

<Brief History of Machine Learning> 介绍:这是一篇介绍机器学习历史的文章,介绍很全面,从感知机.神经网络.决策树.SVM.Adaboost到随机森林.Deep Learning. <Deep Learning in Neural Networks: An Overview> 介绍:这是瑞士人工智能实验室Jurgen Schmidhuber写的最新版本<神经网络与深度学习综述>本综述的特点是以时间排序,从1940年开始讲起,到60-80…

前一篇文章  用 CNTK 搞深度学习 (一) 入门    介绍了用CNTK构建简单前向神经网络的例子.现在假设读者已经懂得了使用CNTK的基本方法.现在我们做一个稍微复杂一点,也是自然语言挖掘中很火的一个模型: 用递归神经网络构建一个语言模型. 递归神经网络 (RNN),用图形化的表示则是隐层连接到自己的神经网络(当然只是RNN中的一种): 不同于普通的神经网络,RNN假设样例之间并不是独立的.例如要预测“上”这个字的下一个字是什么,那么在“上”之前出现过的字就很重要,如果之前出现过“工作”,…

Deep Learning in a Nutshell: Core Concepts This post is the first in a series I’ll be writing for Parallel Forall that aims to provide an intuitive and gentle introduction todeep learning. It covers the most important deep learning concepts and aims…