https://github.com/Hironsan/BossSensor/ 背景介绍 学生时代,老师站在窗外的阴影挥之不去.大家在玩手机,看漫画,看小说的时候,总是会找同桌帮忙看着班主任有没有来. 一转眼,曾经的翩翩少年毕业了,新的烦恼来了,在你刷知乎,看视频,玩手机的时候,老板来了! 不用担心,不用着急,基于最新的人脸识别+手机推送做出的BossComing.老板站起来的时候,BossComing会通过人脸识别发现老板已经站起来,然后通过手机推送发送通知“BossComing”,并且震动告…
Machine and Deep Learning with Python Education Tutorials and courses Supervised learning superstitions cheat sheet Introduction to Deep Learning with Python How to implement a neural network How to build and run your first deep learning network Neur…
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 Learning Research Review Week 2: Reinforcement Learning 转载自: https://adeshpande3.github.io/adeshpande3.github.io/Deep-Learning-Research-Review-Week-2-Reinforcement-Learning This is the 2nd installment of a new series called Deep Learning Resea…
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…
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…
A Full Hardware Guide to Deep Learning Deep Learning is very computationally intensive, so you will need a fast CPU with many cores, right? Or is it maybe wasteful to buy a fast CPU? One of the worst things you can do when building a deep learning sy…
作者:Mingxuan Wang.李航,刘群 单位:华为.中科院 时间:2015 发表于:acl 2015 文章下载:http://pan.baidu.com/s/1bnBBVuJ 主要内容: 用deep learning设计了一种语言模型.可以依据之前"全部"的历史来预測当前词的条件概率.用语言模型迷惑度衡量.用机器翻译衡量,该模型都比baseline(5-gram.RNN.等)好 详细内容: 之前用deep learning在语言模型上的进展是:RNN和LSTM 參考的工具包: R…
下面仅是我的个人认识,说得不正确请轻拍. (眼下,我仅仅看了一些deep learning 的review和TOM Mitchell的书<machine learning>中的神经网络一章.认识有限.感觉3\4讲得一般.勉强一看. 第五章纯粹是为了做笔记,真的不好表达.看不懂还是看tom的书吧. ) 本文的组织: 1.我对deep learning的整体认识 2.发展简史 3.感知器模型 4.感知器的梯度下降训练方法 5.反向传播算法(BP) 1.我对deep learning的整体认识 de…