cazala

synaptic

JavaScript2014–2018

cazala / synaptic

synaptic

architecture-free neural network library for node.js and the browser

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7Distinct people

9Mentions

2Explicit recommenders

6.9KGitHub stars

REPOSITORY AT A GLANCE

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What it is

architecture-free neural network library for node.js and the browser

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

Fascinating. Many years ago, when I wanted to become a programmer and I didn't know anything about code, I used to fantasize and be amazed by programs. Code was like dark…

keyle used a recommendation phrase. 2 indexed comments match. This is a phrase match, not a verdict.

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This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 1:03:20 AM UTC.

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Mentions over time

HN mentions by year9 dated mentions

Observed mentions: 2014-10-27 00:42:04 UTC to 2018-03-30 19:15:14 UTC.

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

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Period	Start (UTC)	End (exclusive, UTC)	Mentions	Submissions	Comments
2014	2014-01-01 00:00:00 UTC	2015-01-01 00:00:00 UTC	1	1	0
2015	2015-01-01 00:00:00 UTC	2016-01-01 00:00:00 UTC	4	1	3
2016	2016-01-01 00:00:00 UTC	2017-01-01 00:00:00 UTC	2	0	2
2017	2017-01-01 00:00:00 UTC	2018-01-01 00:00:00 UTC	1	0	1
2018	2018-01-01 00:00:00 UTC	2019-01-01 00:00:00 UTC	1	0	1

What Hacker News says

4 sources

megalodon·Jul 28, 2015Recommendation phrase

If you haven't already, check out Synaptic [1] by Juan Cazala. I use it in many of my ML projects and it contains a lot of useful examples and documentation. I recommend you take a look at the source as well, which is easy enough to understand. [1] https://github.com/cazala/synaptic

In FANN.js – Fast Artificial Neural Network Compiled with Emscripten

jellekralt·Mar 21, 2015Submission

Synaptic: architecture-free neural network library for Node.js and the browser

1 points · Open discussion

megalodon·Mar 15, 2015

Yes, the success metrics are measured on the training set. I just ran a measurement with a separately generated testing set consisting of 52k characters which yielded a success rate of 98.53% on letters a-z. This turns out to be almost exactly the same as the rate presented on the repo page (98.52%). Will upload the result for your perusal as soon as possible. You will have to browse the synaptic neural network library [1] for an answer to your second question. [1]: https://github.com/cazala/synaptic EDIT: A separate testing set is now generated in addition to the training set. I updated the success rates of the examples in the readme accordingly.

In Show HN: Neural network optical character recognition

megalodon·Mar 9, 2015

Thanks. To answer your first question, I (perhaps naively) assumed that the synaptic library used correct naming for its network prototypes [1]. My implementation contains a few modifications to the one defined as 'Architect.Hopfield' [2], which is why I decided to put it in a separate file. It also helps a visitor to know how the network is defined without needing to browse the source of the synaptic library. [1]: https://github.com/cazala/synaptic/blob/master/README.md#hop... [2]: https://github.com/cazala/synaptic/blob/master/src/architect...

In Show HN: Neural network color recognition