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karpathy
convnetjs
JavaScript2014–2019
karpathy / convnetjs

convnetjs

Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.

10Distinct people
10Mentions
0Explicit recommenders
11.2KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 5:58:02 AM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year10 dated mentions

Observed mentions: 2014-05-09 23:10:19 UTC to 2019-02-21 14:08:24 UTC.

0123452014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 5 mentions; 1 submissions, 4 comments20142015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments20162017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC514
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC202
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC202
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC101

What Hacker News says

2 sources
With all due respect, Karpathy is serious -- and funnily enough he implemented deep learning (convolutional neural nets) in Javascript[1]. Admittedly he did it mainly for fun + browser demos (it's on the front page of Stanford's Convolutional Neural Networks for Visual Recognition course[2], which he is an instructor for), but for learning about the concepts, it's a good enough language. When the students understand the concepts and what they're interested in, then we can nudge them to focus on choice of languages. Even then it's a dangerous domain as there's so many options. Deep learning and want to focus on algorithms or only previously had high level experience? Python with Theano is a good bet and can take advantage of the CPU or GPU. Even Python + numpy. Replicating existing work in the literature and want to take advantage of the s
Read the rest
ome of the existing libraries? Much of it is in Matlab. Doing something crazy on the GPU? C for OpenCL ... The list keeps going, but before getting to any or all of those details, the first step is understanding the concepts. [1]: https://github.com/karpathy/convnetjs [2]: http://cs231n.stanford.edu/
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