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* [https://github.com/rhiever/tpot TPOT]<ref name="tpot1">{{cite journal | vauthors = Olson RS, Urbanowicz RJ, Andrews PC, Lavender NA, Kidd L, Moore JH | year = 2016 | title = Automating biomedical data science through tree-based pipeline optimization | url = https://link.springer.com/chapter/10.1007/978-3-319-31204-0_9 | journal = Proceedings of EvoStar 2016 | volume = 9597 | pages = 123–137 | doi = 10.1007/978-3-319-31204-0_9 | series = Lecture Notes in Computer Science | isbn = 978-3-319-31203-3 }}</ref><ref name="tpot2">{{cite journal | vauthors = Olson RS, Bartley N, Urbanowicz RJ, Moore JH | year = 2016 | title = Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science | url = https://dl.acm.org/citation.cfm?id=2908918 | journal = Proceedings of EvoBIO 2016 | pages = 485–492 | doi = 10.1145/2908812.2908918 | isbn = 9781450342063 }}</ref> is a Python package that automatically creates and optimizes full machine learning pipelines using [[genetic programming]].
* [https://github.com/joeddav/devol devol] is a Python package that performs Deep Neural Network architecture search using [[genetic programming]].
* [https://github.com/DEAP/deap deap] is a Python framework for general evolutionary computation which is flexible and integrates with parallelization packages like scoop and [[Apache Spark|pyspark]], and other Python frameworks like [[Scikit-learn|sklearn]] via [https://github.com/rsteca/sklearn-deap sklearn-deap].
===Other===
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