# sklearn-genetic-opt Projects at AI Tinkerers

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> Markdown URL: https://aitinkerers.org/technologies/sklearn-genetic-opt.md
> Technology record last updated: 2026-04-13T07:36:19Z
> Generated: 2026-09-22T01:44:47Z

Leverage evolutionary algorithms for efficient scikit-learn hyperparameter tuning and robust feature selection.

Sklearn-genetic-opt is your high-performance alternative to standard grid and randomized search methods. The library employs evolutionary algorithms (via the `deap` package) to optimize your scikit-learn model's hyperparameters and features simultaneously. Core components include `GASearchCV` for tuning and `GAFeatureSelectionCV` for feature selection, supporting both regression and classification problems. It also provides essential utilities: custom callbacks for precise control over optimization iterations and built-in plotting functions for visualizing fitness evolution and the search space.

- Official technology site: https://sklearn-genetic-opt.readthedocs.io/
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Genetic Algorithms for AutoML](https://medellin.aitinkerers.org/talks/rsvp_FeI6wXfzC7k)

AutoML is a set of strategies to optimize the process of building machine learning models, common patterns include feature preprocessing, selection, and hyperparameter tuning. Explore the ideas and code behind metaheuristics to build your AutoML pipeline using sklearn-genetic-opt, an open-source library.

- Event context: AI Tinkerers Medellín #2 - 23 de Mayo — 2024-05-23 — Medellín
- Public talk page: https://medellin.aitinkerers.org/talks/rsvp_FeI6wXfzC7k

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