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nidhaloff
igel
Python2020–2021
nidhaloff / igel

igel

a delightful machine learning tool that allows you to train, test, and use models without writing code

3Distinct people
11Mentions
0Explicit recommenders
3.1KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

a delightful machine learning tool that allows you to train, test, and use models without writing code

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 month11 dated mentions

Observed mentions: 2020-09-15 11:34:59 UTC to 2021-06-25 21:11:33 UTC.

012342020-09-01 00:00:00 UTC to 2020-10-01 00:00:00 UTC (exclusive): 2 mentions; 2 submissions, 0 commentsSep 20202020-10-01 00:00:00 UTC to 2020-11-01 00:00:00 UTC (exclusive): 4 mentions; 3 submissions, 1 comments2020-11-01 00:00:00 UTC to 2020-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-12-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2021-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJan 20212021-02-01 00:00:00 UTC to 2021-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-03-01 00:00:00 UTC to 2021-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-04-01 00:00:00 UTC to 2021-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-05-01 00:00:00 UTC to 2021-06-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2021-06-01 00:00:00 UTC to 2021-07-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 commentsJun 2021

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
Sep 20202020-09-01 00:00:00 UTC2020-10-01 00:00:00 UTC220
Oct 20202020-10-01 00:00:00 UTC2020-11-01 00:00:00 UTC431
Nov 20202020-11-01 00:00:00 UTC2020-12-01 00:00:00 UTC000
Dec 20202020-12-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
Jan 20212021-01-01 00:00:00 UTC2021-02-01 00:00:00 UTC000
Feb 20212021-02-01 00:00:00 UTC2021-03-01 00:00:00 UTC000
Mar 20212021-03-01 00:00:00 UTC2021-04-01 00:00:00 UTC000
Apr 20212021-04-01 00:00:00 UTC2021-05-01 00:00:00 UTC000
May 20212021-05-01 00:00:00 UTC2021-06-01 00:00:00 UTC202
Jun 20212021-06-01 00:00:00 UTC2021-07-01 00:00:00 UTC312

What Hacker News says

11 sources
Thanks for the feedback! When I first started the project, it was not thought for production. Just for fast prototyping and experimenting with no efforts at all. However, users liked the tool and started requesting more features including support for serving models and eventually deploying (e.g this issue https://github.com/nidhaloff/igel/issues/62) I agree with your point of vue. However, igel is fairly new and evolving fast. Using igel to serve trained model is a new feature that was implemented in the new release so igel has a long way to go in order to be a solid product for production use.It will surely get more mature with time. Finally, notice that I didn't recommend running it in production. Just mentioned that it is possible and takes no efforts at all. However, if the user generated a trained model then anything can be done with
Read the rest
it from there. Technically, the user can implement his/her own server and use the model as wanted. Obviously, users should do that if they want more control.
In Show HN: Machine learning automation from creating to using models in production
Awesome tool! A few things I found so far: - When running "fit", I get an error when I use the "--yaml_file" parameter mentioned in the readme: "Unrecognized argument -> yaml_file". Using "-yml" works - When using the model for prediction, what format should "path_to_your_test_dataset.csv" be in? Is that a csv in the same format as the training set except for the column we want to predict? Edit: I just found https://github.com/nidhaloff/igel/blob/v0.4.0/examples/data/...
In Show HN: Machine learning automation from creating to using models in production
I think that most companies that sponsor projects are companies that are using the projects. IIUC https://github.com/nidhaloff/igel is your most popular project. Who is using it? Don't expect the companies to pay. You can not force them to pay. It's a project with a MIT license. (Perhaps this is obvious for you, but a few days ago someone posted a rant by another developer because some companies were using his MIT-license project and only making a $500 annual money contribution.) I think one possibility is to write blog post about examples of using the project to solve interesting problems. It's important that they are interesting to get traction here and in other platforms. At the bottom, add a remake explaining that you are the main developer of the project and you'd like sponsors. (I can't guaranty that this will work.) Also, this help
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s as an extended documentation of the project and to get more traffic from google and to get more users. All of that can help to increase the user base and hopefully find an sponsor. (I can't guaranty that this will work.)
In Ask HN: How to find sponsors for my open source projects?
Last year I built deep-translator https://github.com/nidhaloff/deep-translator I wanted a tool where multiple translators are integrated and where I can get translations from different sources but only using one tool. I then tried to build a cross platform mobile app using python (which is not the best language for this, I know) https://github.com/nidhaloff/Translator-pp Probably the best project I built/started last year is the machine learning package igel: https://github.com/nidhaloff/igel
In Ask HN: What are some tools / libraries you built yourself?

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