karpathy.github.io
Andrej Karpathy blogMusings of a Computer Scientist.
http://karpathy.github.io/
Musings of a Computer Scientist.
http://karpathy.github.io/
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https://karpathy.github.io
Musings of a Computer Scientist.
karpathy.github.io
Quantifying Hacker News with 50 days of data
http://karpathy.github.io/2013/11/27/quantifying-hacker-news
Hacker's guide to Neural Networks. Quantifying Hacker News with 50 days of data. Nov 27, 2013. I thought it would be fun to analyze the activity on one of my favorite sources of interesting links and information, Hacker News. I set up a very simple python script that scrapes the HN front page. And the new stories page. Raw HTML data parsing. The parsing Python script uses BeautifulSoup. U'play.google.com',. U'https:/ play.google.com/store/devices/details? Id=nexus 5 black 16gb',.
What I learned from competing against a ConvNet on ImageNet
http://karpathy.github.io/2014/09/02/what-i-learned-from-competing-against-a-convnet-on-imagenet
Hacker's guide to Neural Networks. What I learned from competing against a ConvNet on ImageNet. Sep 2, 2014. The results of the 2014 ImageNet Large Scale Visual Recognition Challenge. A few days ago. The New York Times wrote about it. Too ILSVRC is one of the largest challenges in Computer Vision and every year teams compete to claim the state-of-the-art performance on the dataset. The challenge is based on a subset of the ImageNet dataset that was first collected by Deng et al. 2009. For the purposes of...
Breaking Linear Classifiers on ImageNet
http://karpathy.github.io/2015/03/30/breaking-convnets
Hacker's guide to Neural Networks. Breaking Linear Classifiers on ImageNet. Mar 30, 2015. You’ve probably heard that Convolutional Networks work very well in practice and across a wide range of visual recognition problems. You may have also read articles and papers that claim to reach a near. There are all kinds of caveats to that (e.g. see my G post on Human Accuracy is not a point, it lives on a tradeoff curve. ConvNets. See the image below for an illustration:. By Goodfellow et al. By Nguyen et al....
The Unreasonable Effectiveness of Recurrent Neural Networks
http://karpathy.github.io/2015/05/21/rnn-effectiveness
Hacker's guide to Neural Networks. The Unreasonable Effectiveness of Recurrent Neural Networks. May 21, 2015. There’s something magical about Recurrent Neural Networks (RNNs). I still remember when I trained my first recurrent network for Image Captioning. We’ll train RNNs to generate text character by character and ponder the question how is that even possible? By the way, together with this post I am also releasing code on Github. Depending on your background you might be wondering:. Sequence input (e&...
Hacker's guide to Neural Networks
http://karpathy.github.io/neuralnets
Hacker's guide to Neural Networks. Hacker's guide to Neural Networks. 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. 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 suspended my work o...
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DANIEL SLATER'S BLOG: Using Net2Net to speed up network training
http://www.danielslater.net/2016/05/using-net2net-to-speed-up-network.html
Thursday, May 26, 2016. Using Net2Net to speed up network training. When training neural networks there are 2 things that combine to make life frustrating:. Neural networks can take an insane amount of time of train. If a network could be trained quickly number 2 wouldn't really matter, we could just do a grid search(or even particle swarm optimization. Or maybe Bayesian optimization. The amount of time to train is counted in days so better hope your first guess was good. I have posted a numpy implementa...
DANIEL SLATER'S BLOG: June 2015
http://www.danielslater.net/2015_06_01_archive.html
Thursday, June 18, 2015. Why there is a big unsupervised learning shaped whole in the universe. Unfortunately so far we are a long way from that and the technique shown here seems trivial compared to that goal. But the goal is interesting enough that it is worth pursuing. The answer to the question "what am I asking an unsupervised network to do? An example competitive learning neural net. It is also available in C#. From random import uniform class UnsupervisedNN(object): def init (self, size of input a...
DANIEL SLATER'S BLOG: October 2015
http://www.danielslater.net/2015_10_01_archive.html
Tuesday, October 27, 2015. Even more quick summaries of research papers. Following on from part 1. Here are even more quick summaries of research papers,. Generative NeuroEvolution for DeepLearning. Uses the MNIST hand-drawn digits dataset, trains both a normal deep network and a convolutional network. HyperNEAT on it's own performs very badly. Using HyperNEAT to generate a number of layers and then backprop on the final layer is achieves 58.4% for normal ANNs. ES-HyperNeat uses the connection weights va...
DANIEL SLATER'S BLOG: August 2015
http://www.danielslater.net/2015_08_01_archive.html
Saturday, August 29, 2015. Presenting WikiDataDotNet - Client API for WikiData. Is one of those things that sets the mind boggling at the possibilities of the internet. It's a project, started by the WikiMedia foundation, to collect structured data on everything. If you are doing anything related to machine learning, it is the best source of data I have so far found. Https:/ www.wikidata.org/w/api.php? This will return a JSON file with sections like:. Here we see the id of the item, in this case Q38.
DANIEL SLATER'S BLOG: Deep-Q learning Pong with Tensorflow and PyGame
http://www.danielslater.net/2016/03/deep-q-learning-pong-with-tensorflow.html
Sunday, March 13, 2016. Deep-Q learning Pong with Tensorflow and PyGame. In a previous post. We went built a framework for running learning agents against PyGame. Now we'll try and build something in it that can learn to play Pong. We will be aided in this quest by two trusty friends Tensorflow. Google's recently released numerical computation library and this paper. On reinforcement learning for Atari games by Deepmind. Is a good starting point for learning. You will need Python 2 or 3 installed. In the...
DANIEL SLATER'S BLOG: May 2016
http://www.danielslater.net/2016_05_01_archive.html
Thursday, May 26, 2016. Using Net2Net to speed up network training. When training neural networks there are 2 things that combine to make life frustrating:. Neural networks can take an insane amount of time of train. If a network could be trained quickly number 2 wouldn't really matter, we could just do a grid search(or even particle swarm optimization. Or maybe Bayesian optimization. The amount of time to train is counted in days so better hope your first guess was good. I have posted a numpy implementa...
DANIEL SLATER'S BLOG: Mini-Pong and Half-Pong
http://www.danielslater.net/2016/05/mini-pong-and-half-pong.html
Monday, May 2, 2016. I'm going to be giving a talk/tutorial at PyDataLondon 2016. On Friday the 6th of may, if your in London that weekend I would recommend going, there are going to be lots of interesting talks, and if you do go please say hi. Possibly they are using other tricks not reported in the paper, or just lots of hyper parameter tuning, or there are still more bugs in my implementation(entirely possible, if anyone finds any please submit). Distance from building our future robot overlords, stil...
A Quick Guide to Installing TensorFlow on mac OS - The Asimov Institute
http://www.asimovinstitute.org/a-quick-guide-to-installing-tensorflow-on-mac-os
A Quick Guide to Installing TensorFlow on mac OS. June 15, 2016. June 15, 2016. By Fjodor van Veen. TL;DR: paste all the commands in your terminal in order of appearance; skip packages you already have (but update them). First we install Homebrew (brew). Brew makes it really easy to install a very, very large amount of different packages. Installing brew is really simple:. Usr/bin/ruby -e “$(curl -fsSL https:/ raw.githubusercontent.com/Homebrew/install/master/install)”. Sudo easy install pip. Next up is ...
The Great Cognitive Escape: Clojure Data Analysis Cookbook - a Book Review
http://blog.carsoncheng.ca/2013/07/clojure-data-analysis-cookbook-book.html
The Great Cognitive Escape. Notes and thoughts on programming, Linux, computing science, teaching, student and machine learning, artificial intelligence, etc. Clojure Data Analysis Cookbook - a Book Review. I was recently asked to review Clojure Data Analysis Cookbook. Data analysis has been one of the "selling points" of Clojure as a practical language. A practical lisp for practical data analysis. Similarly, I'd say you had best be familiar with how to do data analysis as a discipline in itself. If...
The Great Cognitive Escape: May 2015
http://blog.carsoncheng.ca/2015_05_01_archive.html
The Great Cognitive Escape. Notes and thoughts on programming, Linux, computing science, teaching, student and machine learning, artificial intelligence, etc. Getting sidelined: Computing Science vs Engineering degrees. Engineers: please stop telling people what to do with their own lives. This is speaking to the Computer, Electrical, or so-called Software Engineers out there, but really, this applies to those in any engineering field, e.g. including Petroleum Engineers. 160;Well, why don’t we have...
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Karpathosvilla Wonderful Villa in Kyra Panagia, Karpathos (Greece) for Rent
The beach of Kyra Panagia. The large kitchen, fully equipped, has four burner gas cooker with cooker hood, two sinks, a large kitchen desk, a refrigerator, two freezers, kitchen cabinets and cupboards, tables, chairs, dishes, glasses, pots, pans and kitchen cutlery. There are three bedrooms divided into two double rooms and one room with a bunk bed and a single bed. Also, there are wardrobes,chests of drawers, air conditioning, television and a bathroom with shower. Period from 01/03 to 31/03. Write us w...
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Calgary SEO Best Search Engine Optimization. Calgary Search Engine Optimization Tips. April 12, 2015. Google has used a number of factors to affect your website’s rankings; the lesser known factors and ever changing criteria are why you need a Calgary SEO company to help you stay on the front page. The Uncertain Future of Google’s Arbitration of Truth In 2015, Google announced it would judge websites based on. Calgary Search Engine Optimization. Proudly powered by WordPress.
Karpathy (Csaba (Max) Zsilvolgyi) - DeviantArt
Window.devicePixelRatio*screen.width 'x' window.devicePixelRatio*screen.height) :(screen.width 'x' screen.height) " class="mi". Window.devicePixelRatio*screen.width 'x' window.devicePixelRatio*screen.height) :(screen.width 'x' screen.height) ". Join DeviantArt for FREE. Forgot Password or Username? Deviant for 6 Years. This deviant's full pageview. Last Visit: 284 weeks ago. This is the place where you can personalize your profile! By moving, adding and personalizing widgets. Why," you ask? Mar 11, 2010.
Andrej Karpathy blog
Hacker's guide to Neural Networks. May 21, 2015. The Unreasonable Effectiveness of Recurrent Neural Networks. We'll train and sample from character-level RNN language models that learn to write poetry, latex math and code. We'll also analyze the models and get hints of future research directions. Mar 30, 2015. Breaking Linear Classifiers on ImageNet. Sep 2, 2014. What I learned from competing against a ConvNet on ImageNet. Aug 3, 2014. Jul 3, 2014. Jul 2, 2014. A writeup of a recent mini-project: I scrap...
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