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A collection of teaching materials, code, and data for data analysis and machine learning projects with accompanying blog posts.
A Python framework for gradient-free optimization, featuring common algorithms like genetic algorithms and simulated annealing.
A fast and flexible Rust library for implementing genetic algorithms, neuroevolution, and genetic programming.
An extensible .NET genetic algorithm library for optimization and AI, making evolutionary computation simple.
A comprehensive Ruby gem providing atomic, flexible tools and frameworks for practical machine learning applications.
A comprehensive Ruby gem providing a collection of atomic machine learning tools and frameworks for practical applications.
A simple Ruby implementation of a genetic algorithm for solving the 1-max problem, designed for educational demonstrations.
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