{"id":15538590,"url":"https://github.com/n3pdf/evolutionary_keras","last_synced_at":"2025-04-23T15:24:52.217Z","repository":{"id":55383294,"uuid":"228861797","full_name":"N3PDF/evolutionary_keras","owner":"N3PDF","description":"An evolutionary algorithm implementation for Keras","archived":false,"fork":false,"pushed_at":"2021-01-04T10:24:16.000Z","size":166,"stargazers_count":10,"open_issues_count":10,"forks_count":7,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-04-14T23:22:07.786Z","etag":null,"topics":["evolutionary-algorithm","genetic-algorithm","keras","machine-learning","open-source","python","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/N3PDF.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-12-18T14:51:40.000Z","updated_at":"2024-06-19T11:08:32.000Z","dependencies_parsed_at":"2022-08-14T23:01:08.184Z","dependency_job_id":null,"html_url":"https://github.com/N3PDF/evolutionary_keras","commit_stats":null,"previous_names":[],"tags_count":5,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/N3PDF%2Fevolutionary_keras","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/N3PDF%2Fevolutionary_keras/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/N3PDF%2Fevolutionary_keras/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/N3PDF%2Fevolutionary_keras/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/N3PDF","download_url":"https://codeload.github.com/N3PDF/evolutionary_keras/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":250458563,"owners_count":21433898,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["evolutionary-algorithm","genetic-algorithm","keras","machine-learning","open-source","python","tensorflow"],"created_at":"2024-10-02T12:04:59.904Z","updated_at":"2025-04-23T15:24:52.195Z","avatar_url":"https://github.com/N3PDF.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3630339.svg)](https://doi.org/10.5281/zenodo.3630339)\n[![](https://github.com/N3PDF/evolutionary_keras/workflows/pytest/badge.svg)](https://pypi.org/project/evolutionary-keras/)\n[![Documentation Status](https://readthedocs.org/projects/evolutionary-keras/badge/?version=latest)](https://evolutionary-keras.readthedocs.io/en/latest/?badge=latest)\n[![Anaconda-Server Badge](https://anaconda.org/conda-forge/evolutionary_keras/badges/installer/conda.svg)](https://anaconda.org/conda-forge/evolutionary_keras)\n\n\n# evolutionary_keras\n\nKeras is one of the most widely used Machine Learning frameworks available in the market. It is a high-level API written in Python and that can run on mulitple backends. Their goal is to be able to build and test new model as fast as possible.\n\nKeras models are trained through the usage of optimizers, all of which are Gradient Descent based. This module deals with that shortcoming of Keras by implementing several Evolutionary Algorithms on top of Keras while keeping the main philosophy of the project: it must be easy to prototype.\n\nThe default project library now provides support for:\n- Nodal Genetical Algorithm (NGA)\n- Covariance Matrix Adaptation Evolution Strategy (CMA-ES)\n\n## Installation\n\nevolutionary_keras is available to install from pip and conda using the following commands:\n\n```bash\n    pip install evolutionary-keras\n    conda install evolutionary_keras -c conda-forge\n```\n\nAfter which it can readily be imported in your python project\n\n```python\n    import evolutionary_keras\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fn3pdf%2Fevolutionary_keras","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fn3pdf%2Fevolutionary_keras","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fn3pdf%2Fevolutionary_keras/lists"}