Enterprise DNAEnterprise DNA

Open Source

automl-gs

Provide an input CSV and a target field to predict, generate a model + code to run it.

Our verdict

Not reviewed yet

We have not reviewed automl-gs yet

No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.

How we review records

From the listing

About automl-gs

automl-gs is an open-source Python tool that takes a CSV file and a target field, then automatically generates a machine learning model and the code to run it. It uses genetic search to explore model architectures and hyperparameters, producing a ready-to-use script without manual tuning.

Best for

Data scientists and developers who want a quick, code-generating AutoML baseline for tabular data.

Use cases

  • Quickly prototype a model from a CSV dataset for classification or regression
  • Generate baseline code for a predictive model to refine further
  • Automate model selection and hyperparameter search for small to medium datasets

Notes

1,866 stars on GitHub. Last updated 2019-10-22. Licensed MIT.

Pros

  • Produces executable Python code, not just a black-box model
  • Simple input format (CSV + target field) lowers the barrier to entry
  • Genetic algorithm approach can discover non-obvious model configurations

Cons

  • Genetic search can be computationally expensive for large datasets
  • Limited to tabular data from CSV inputs
  • Community project with 1,866 stars, not actively maintained by a large team

Key facts

What we have checked

Latest version
0.2.1 (released 5 Apr 2019)
Checked GitHub
Days since the last commit
2,572
Checked GitHub
GitHub forks
178
Checked GitHub
GitHub stars
1,867
Checked GitHub
Days to a first reply on issues
2115.1
Checked GitHub
Open issues
25
Checked GitHub
Releases in the last 90 days
0
Checked GitHub

Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.

Stars and usage

How automl-gs is growing

GitHub stars

1,866 to 1,867

stars. 12 July 2026 to 7 Nov 2026, 3 readings.

Source: GitHub. Checked .

Health and security

Is automl-gs looked after, and what do its setup files show

Health score

0 out of 100

Does someone look after this repository? It does not say the code is good or safe. Worked out from GitHub signals checked . How it is worked out

PartPointsWhat we saw
Recent activity0 of 30Last push 2,572 days ago
Releases0 of 150 releases in 90 days
Issue replies0 of 20First reply in 2115.1 days (median)
Maintainer0 of 15Owned by a single user
Official sourceNot countedMCP servers only

Sources

Where this comes from

  • GitHubRegistry

    Checked · Days since the last commit, GitHub forks, GitHub stars, Days to a first reply on issues, Open issues, Releases in the last 90 days

  • GitHubOfficial

    Checked · Latest version

A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.

Changelog

What changed

  1. Released 0.2.1

    Source: GitHub

  2. Released 0.2

    Source: GitHub

Pairs with

Other entries in the index that connect to this one. Click through to see the chain.

Free 27-page guide

Get the free Developer’s Field Guide

A 27-page field guide to the AI coding workflow with Claude. Claude Code, MCP servers, the prompt patterns that work, and what to delegate. Free.

Enter your work email. We send it straight over, plus a few short notes worth knowing. Unsubscribe any time.

No spam. Unsubscribe any time.