Optimization Foundations
This project applies optimization techniques using NumPy to optimize multidimensional functions. Key algorithms covered include Gradient Descent, Linear Minimization, Newton's Method and Conjugate Gradient.
Neural Networks Foundations
This project implements neural networks using NumPy to solve regression and classification problems. Key algorithms covered include Perceptron, ADALINE and Multi-Layered Perceptron (MLP).