This repository showcases the coursework from the Computational Intelligence course completed at Vrije University during Spring 2023.
- Exploration of gradient-based and derivative-free optimization methods. The project focuses on minimizing a complex function, providing insights into the nuances of optimization techniques in computational intelligence.
- Implementation of Metropolis-Hastings and Simulated Annealing algorithms. The assignment offers a comparative study of these methods applied to a mixture of Gaussians, showcasing their behaviors and differences.
- Application of evolutionary algorithms to a non-differentiable optimization task. This project includes the development and analysis of recombination and mutation operators, along with selection mechanisms, focusing on optimizing a black-box function.
- Implementation of fully-connected and convolutional neural networks using PyTorch for image classification. This project emphasizes the understanding of neural network architectures, optimizers, and loss functions in deep learning.