Machine Learning Class Projects: (Python)
Project 1: Batch K-means, Online K-means, Image Segmentation by K-means, KNN Classification
Project 2: Least Square Classification (2 classes), Least Square Classification (3 classes), MAximum mean projection classification
Project 3: Perceptron Model, Online Perceptron Learning, Batch Perceptron Learning, Gradient Descent with A Quadratic Cost Function, Gradient Descent with A QRosenbrock's Cost Function, Gradient Descent with A Himmelblau's Cost Function, Newton's Method with Quadratic Cost Function, Levenberg-MArquardt Method with Himmelblau's Cost Function
Project 4: Multi-Layer Perceptron on Double Moon Dataset, Multi-Layer Perceptron on Gaussian XOR Dataset, Model Validation, Autoencoder-Based Image Compression/Filtering, Principle Component Analysis
Project 5: Contextual Maps Using Self-Organizing-Map, Density Estimation, Classification Using Density Estimation
Project 6: Decision Trees, MLP on MNIST