partical-swarm-optimization

Stock Portfolio Optimization with Bayesian shrinkage, DRIP, Projected vs Actual perfomenace and Blume-Adjusted Betas

This repository contains work for CSCI 447 Introduction to Machine Learning. It represent a wide range of machine learning algorithms and principles, implemented from scratch by Braeden Hunt and Tyler Koon (group 6).

These are a couple katas attempting at solving the N Queens problem set using diffrent algorithms and huristics.

In this project, we executed an optimized architecture for image recognition on the CIFAR-10 dataset using the Particle Swarm Optimization (PSO) method.

🚀 Reinforcement learning from scratch — including value-based and policy-based methods, alongside search-driven approaches from evolutionary strategies like Genetic Algorithms to adaptive techniques like Simulated Annealing, PSO, and CMA-ES

Bu proje, modern meta-sezgisel (meta-heuristic) optimizasyon algoritmalarının performansını, ölçeklenebilirliğini ve istatistiksel güvenilirliğini karşılaştırmalı olarak analiz eder.

Archiving a miscellaneous study

An experimental optimization project comparing classical and metaheuristic methods, applying a modified legacy EvoloPy framework to wrapper-based feature selection, and evaluating PSO with stagnation-aware early stopping.