automl-gs

Overview

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

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

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.

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

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

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

Indexed from awesome-llmops and enriched against its public facts.