minimaxir/automl-gs
Provide an input CSV and a target field to predict, generate a model + code to run it. observed · 2026-08-28
Health v2 · maintenance only
23/100
- Activity 0
- Release rhythm 8
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2789
- days_rel: n/a
- days_push: 2507
- n_releases_24m: 0
Adoption not part of the score
1866 stars · 180 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
automl-gs is a Python AutoML tool that takes an input CSV and a target prediction field and automatically generates a trained machine learning or deep learning model along with native Python pipeline code. It abstracts data transformation, model architecture, and hyperparameter search across frameworks like TensorFlow/Keras and XGBoost with no black-box lock-in.
Use cases
- predict a target column from a csv without writing model code
- generate a baseline model for tabular data automatically
- get native python code for a trained prediction pipeline
- run automated hyperparameter search on a dataset
- build ml models without deep statistical knowledge
- export a model pipeline with no platform lock-in
When to choose
- you have tabular csv data and want a strong baseline model quickly
- you want readable, editable generated code instead of a black-box model
- you're a citizen data scientist without deep ML engineering experience
- you want to train models cheaply using TPUs in Google Colaboratory
When to avoid
- you need state-of-the-art model performance beyond strong baselines
- you need actively maintained tooling with recent updates
- your data is unstructured like images, audio, or free text
- you need a full AutoML platform with extensive framework support
Facets
library · maturity maintenance
machine-learning deep-learning data-science etl machine-learning data-science python cli cross-platform automl tabular-data hyperparameter-search code-generation tensorflow xgboost citizen-data-science automation
2 sources
- readme: https://github.com/minimaxir/automl-gs · fetched 2026-08-28 · 96ac7022f6f4
- registry_pypi: https://pypi.org/pypi/automl-gs/json · fetched 2026-08-29 · c1966bccafbf
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| minimaxir/automl-gs | main | 23 |
For agents
markdown · JSON · MCP: product_card(name="minimaxir/automl-gs")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem