MetaSklearn: A Metaheuristic-Powered Hyperparameter Optimization Framework for Scikit-Learn Models.
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Updated
Jun 4, 2025 - Python
MetaSklearn: A Metaheuristic-Powered Hyperparameter Optimization Framework for Scikit-Learn Models.
Built for the implementation of Keras in Tensorflow. Behaves similarly to GridSearchCV and RandomizedSearchCV in Sci-Kit learn, but allows for progress to be saved between folds and for fitting and scoring folds in parallel.
Nine Mens Morris (Human vs AI) implemented in Python by using Alpha–Beta Pruning algorithm and Randomized Search Heuristics.
Compare time complexity of binary search algorithm and randomized search algorithm to search for 1000 keys in a sorted array
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