Hacker's guide to Neural Networks


345 bookmarks. First posted by arsyed august 2014.


Hi there, I’m a CS PhD student at Stanford. I’ve worked on Deep Learning for a few years as part of my research and among several of my related pet projects is ConvNetJS - a Javascript library for training Neural Networks.
migrate  pocket  pocket2 
29 days ago by patgardner
Hacker's guide to Neural Networks
1707  dev  ai 
7 weeks ago by rdslw
Musings of a Computer Scientist.
9 weeks ago by jmcd
Hi there, I’m a CS PhD student at Stanford . I’ve worked on Deep Learning for a few years as part of my research and among several of my related pet projects is…
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10 weeks ago by disnet
RT : Hacker's guide to Neural Networks
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10 weeks ago by geeknik
Hi there, I’m a CS PhD student at Stanford. I’ve worked on Deep Learning for a few years as part of my research and among several of my related pet projects is ConvNetJS - a Javascript library for training Neural Networks.
10 weeks ago by sgreenlay
Hacker's guide to Neural Networks :
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10 weeks ago by vdm
This article (which I plan to slowly expand out to lengths of a few book chapters) is my humble attempt.
javascript  deep-learning 
10 weeks ago by Tafkas
via hacker news
javascript  ml 
10 weeks ago by randykarels
Hi there, I’m a CS PhD student at Stanford. I’ve worked on Deep Learning for a few years as part of my research and among several of my related pet projects is ConvNetJS - a Javascript library for training Neural Networks. via Pocket
IFTTT  Pocket  deep-learning 
june 2017 by chakkakuru
Hacker's guide to Neural Networks - Added March 02, 2015 at 09:53AM
machine-learning  neural-networks  read2of 
april 2017 by xenocid
to-read
april 2017 by anas
A great guide to Neural Networks. Low on math, and provides intuition.
neuralnets  gradientdescent  backpropagation  tutorial  explanation  machinelearning  neuralnetworks  javascript  programming 
november 2016 by drmeme
My personal experience with Neural Networks is that everything became much clearer when I started ignoring full-page, dense derivations of backpropagation equations and just started writing code. Thus, this tutorial will contain very little math (I don’t believe it is necessary and it can sometimes even obfuscate simple concepts). Since my background is in Computer Science and Physics, I will instead develop the topic from what I refer to as hackers’s perspective. My exposition will center around code and physical intuitions instead of mathematical derivations. Basically, I will strive to present the algorithms in a way that I wish I had come across when I was starting out.
ai  neural-networks  machine-learning  ml  todo 
september 2016 by hellsten
Hacker's Guide to Neural Networks - Andrej Karpathy's blog
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september 2016 by randallr
Musings of a Computer Scientist.
july 2016 by vgeddes
Hi there, I’m a CS PhD student at Stanford. I’ve worked on Deep Learning for a few years as part of my research and among several of my related pet projects is ConvNetJS - a Javascript library for training Neural Networks.
Pocket  ai 
june 2016 by iiska
Hi there, I
june 2016 by probablytom
Your calculus too rusty to understand backprop? Here's a hacker's explanation: http://karpathy.github.io/neuralnets/. #machinelearning #DeepLearning
may 2016 by amy