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Source channel @githubtrending · Post #15242 · Oct 23

#python#ant_colony_algorithm#artificial_intelligence#fish_swarms#genetic_algorithm#heuristic_algorithms#immune#immune_algorithm#optimization#particle_swarm_optimization#pso#simulated_annealing#travelling_salesman_problem#tsp You can use scikit-opt, a Python library offering many heuristic optimization algorithms like Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony, Immune Algorithm, and Artificial Fish Swarm Algorithm. It supports user-defined functions to customize operators, allows continuing runs from previous iterations, and accelerates computations via vectorization, multithreading, multiprocessing, and caching. GPU support is in development. It helps solve complex optimization problems such as function minimization and the Traveling Salesman Problem efficiently, with easy installation and rich examples. This saves you time and effort in implementing and tuning optimization algorithms yourself. https://github.com/guofei9987/scikit-opt

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@githubtrending · Post #14809 · 06/08/2025, 01:30 PM

#ruby#beginners#hacktoberfest#hacktoberfest2020#helm#kubernetes#kubetools Kubernetes is a powerful tool for managing containerized applications. To learn Kubernetes, you can use platforms like Kubelabs, which offer interactive tutorials and labs. These resources help you understand Kubernetes concepts from the basics to advanced levels. By using these platforms, you can practice deploying applications, managing resources, and ensuring high availability and scalability. This hands-on approach helps you gain practical experience and improve your skills in managing complex applications efficiently. https://github.com/collabnix/kubelabs