MessageInABottle
@mib_messageinabottle · Post #7052 · 06/11/2024, 01:45 PM
The #MRNA "#vaccine" was never a real vaccine but a #BioWeapon meant to #attack your #immune system
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Source channel @githubtrending · Post #14952 · Jul 13
#go#go_interview_questions#go_practice#golang#golang_interview_questions#golang_practice#hacktoberfest#interview#interview_practice#interview_questions#learn_to_code#learning_resources You can practice and improve your Go programming skills with an interactive web platform that offers 30 coding challenges ranging from beginner to advanced levels. It provides a live code editor with syntax highlighting, instant test results, and detailed performance analytics to help you write efficient Go code. You can track your progress on leaderboards, compare your solutions with others, and learn from detailed explanations and resources for each challenge. The platform supports easy setup via web UI, GitHub Codespaces, or command line, making it convenient to prepare for Go technical interviews and boost your coding confidence. This helps you master Go concepts and get ready for real job interviews effectively. https://github.com/RezaSi/go-interview-practice
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@githubtrending · Post #15242 · 10/23/2025, 12:30 PM
#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