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dmlc
mxnet.js
JavaScript2015–2018
dmlc / mxnet.js

mxnet.js

MXNetJS: Javascript Package for Deep Learning in Browser (without server)

3Distinct people
3Mentions
0Explicit recommenders
434GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

MXNetJS: Javascript Package for Deep Learning in Browser (without server)

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 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM 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 month3 dated mentions

Observed mentions: 2015-12-04 08:12:18 UTC to 2018-03-30 19:15:14 UTC.

012015-12-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsDec 20152016-01-01 00:00:00 UTC to 2016-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-02-01 00:00:00 UTC to 2016-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-03-01 00:00:00 UTC to 2016-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-04-01 00:00:00 UTC to 2016-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-05-01 00:00:00 UTC to 2016-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-06-01 00:00:00 UTC to 2016-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-07-01 00:00:00 UTC to 2016-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-01 00:00:00 UTC to 2016-09-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2016-09-01 00:00:00 UTC to 2016-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-10-01 00:00:00 UTC to 2016-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-11-01 00:00:00 UTC to 2016-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-12-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-01 00:00:00 UTC to 2017-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJan 20172017-02-01 00:00:00 UTC to 2017-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-03-01 00:00:00 UTC to 2017-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-04-01 00:00:00 UTC to 2017-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-05-01 00:00:00 UTC to 2017-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-06-01 00:00:00 UTC to 2017-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-07-01 00:00:00 UTC to 2017-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-08-01 00:00:00 UTC to 2017-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-09-01 00:00:00 UTC to 2017-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-10-01 00:00:00 UTC to 2017-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-11-01 00:00:00 UTC to 2017-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-12-01 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 2018-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-02-01 00:00:00 UTC to 2018-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-03-01 00:00:00 UTC to 2018-04-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsMar 2018

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
Dec 20152015-12-01 00:00:00 UTC2016-01-01 00:00:00 UTC110
Jan 20162016-01-01 00:00:00 UTC2016-02-01 00:00:00 UTC000
Feb 20162016-02-01 00:00:00 UTC2016-03-01 00:00:00 UTC000
Mar 20162016-03-01 00:00:00 UTC2016-04-01 00:00:00 UTC000
Apr 20162016-04-01 00:00:00 UTC2016-05-01 00:00:00 UTC000
May 20162016-05-01 00:00:00 UTC2016-06-01 00:00:00 UTC000
Jun 20162016-06-01 00:00:00 UTC2016-07-01 00:00:00 UTC000
Jul 20162016-07-01 00:00:00 UTC2016-08-01 00:00:00 UTC000
Aug 20162016-08-01 00:00:00 UTC2016-09-01 00:00:00 UTC101
Sep 20162016-09-01 00:00:00 UTC2016-10-01 00:00:00 UTC000
Oct 20162016-10-01 00:00:00 UTC2016-11-01 00:00:00 UTC000
Nov 20162016-11-01 00:00:00 UTC2016-12-01 00:00:00 UTC000
Dec 20162016-12-01 00:00:00 UTC2017-01-01 00:00:00 UTC000
Jan 20172017-01-01 00:00:00 UTC2017-02-01 00:00:00 UTC000
Feb 20172017-02-01 00:00:00 UTC2017-03-01 00:00:00 UTC000
Mar 20172017-03-01 00:00:00 UTC2017-04-01 00:00:00 UTC000
Apr 20172017-04-01 00:00:00 UTC2017-05-01 00:00:00 UTC000
May 20172017-05-01 00:00:00 UTC2017-06-01 00:00:00 UTC000
Jun 20172017-06-01 00:00:00 UTC2017-07-01 00:00:00 UTC000
Jul 20172017-07-01 00:00:00 UTC2017-08-01 00:00:00 UTC000
Aug 20172017-08-01 00:00:00 UTC2017-09-01 00:00:00 UTC000
Sep 20172017-09-01 00:00:00 UTC2017-10-01 00:00:00 UTC000
Oct 20172017-10-01 00:00:00 UTC2017-11-01 00:00:00 UTC000
Nov 20172017-11-01 00:00:00 UTC2017-12-01 00:00:00 UTC000
Dec 20172017-12-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
Jan 20182018-01-01 00:00:00 UTC2018-02-01 00:00:00 UTC000
Feb 20182018-02-01 00:00:00 UTC2018-03-01 00:00:00 UTC000
Mar 20182018-03-01 00:00:00 UTC2018-04-01 00:00:00 UTC101

What Hacker News says

3 sources
For anyone interested, here is a sampling of available ML libs in JavaScript. The first two, including tensorflow.js, are sub-libraries of the major ML projects, and the others are custom JS libs: [tensorflow.js](https://github.com/tensorflow/tfjs) [mxnet.js](https://github.com/dmlc/mxnet.js/) [propel.js](https://github.com/propelml/propel) - this uses tensorflow.js under the hood [ml5](https://github.com/ml5js/ml5-library) - also uses tensorflow.js [webdnn](https://github.com/mil-tokyo/webdnn) [brain.js](https://github.com/BrainJS/brain.js) [mljs](https://github.com/mljs/ml) [synaptic](https://github.com/cazala/synaptic) edit: added the ml5 lib mentioned in a subsequent comment.
In Introducing TensorFlow.js: Machine Learning in JavaScript
Nice work! I've also tried my hands at use WebGL to do deep learning in the browser (e.g. https://github.com/scienceai/neocortex/blob/master/src/lib/w...). The conclusion I came to was that there are just way too many limitations for it to really pay off. The need to encode everything in textures etc limits the data shape and dimensionality, not to mention the complexity cost. If you can get more complex networks working I'll be really impressed! MXnet.js [1] is an emscripten port of the base C++ framework. It runs entirely in the browser and works fairly well. The actual code produced by emscripten isn't that large, but the model weights can become an issue. I've tried to get emscripten working on tensorflow, even just for forward prediction, but have been pretty much gotten nowhere. Of course this doesn't let you harness GPU power. Lots
Read the rest
of cool potential applications of doing deep learning over the web are just waiting to be discovered and built. [1] https://github.com/dmlc/mxnet.js
In Show HN: GPU-Accelerated Digit Recognition with WebGL

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