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New release of Gradient-Free-Optimizers with two new evolutionary algorithms
Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces. - SimonBlanke/Gradient-Free-Optimizers
Master status:Code quality:Latest versions: Gradient-Free-Optimizers provides a collection of easy to use optimization techniques, whose objective function only requires an arbitrary score that gets maximized. Convex FunctionNon-convex FunctionDifferential Evolution Improves a population of candidate solutions by creating trial vectors through the differential mutation of three randomly selected individuals. Search-Data-Explorer Visualize search-data with plotly inside a streamlit dashboard.If you want news about Gradient-Free-Optimizers and related projects you can follow me on twitter.
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