Distributed Evolutionary Algorithms in Python (DEAP) is a novel evolutionary computation framework for rapid prototyping and testing of ideas.
Pros
- Highly customizable
- Supports parallelization
Cons
- Steep learning curve
- Requires Python knowledge
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FlatGA is a lightweight genetic algorithm library for Python.
Distributed Evolutionary Algorithms in Python (DEAP) is a novel evolutionary computation framework for rapid prototyping and testing of ideas.
Pyevolve is a pure Python genetic algorithm framework that provides a set of methods for function optimization.
Tree-based Pipeline Optimization Tool (TPOT) is an automated machine learning tool that optimizes machine learning pipelines using genetic programming.
COCO (COmparing Continuous Optimisers) is a platform for systematic and sound comparisons of real-parameter global optimisers. It provides benchmark functions, easy interfaces...
PyCaret is an open-source, low-code Python library for automating machine learning workflows, including data preparation, model comparison, tuning, and deployment. It is...
Free, open source
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