AI Based Parameter Estimation of ML Models

Optimizing hyperparameters is crucial for enhancing the performance of machine learning models. This project presents a hybrid optimization algorithm that combines Genetic Algorithm (GA) and Simulated Annealing (SA) to efficiently search and fine-tune hyperparameters, leading to more accurate and robust models.

Visit: https://pypi.org/project/jss-optimizer/ to try it out

Technologies Used:

Programming Language: Python
Optimization Algorithms: Genetic Algorithm (GA), Simulated Annealing (SA)
Software Development: “PIP” Python packaging for easy distribution and integration