Pattern-Recognition

Project 1

• Probability theory - Bayesian Decision Theory
• Probabilistic Classifiers

Project 2

• Non Parametric Estimation (Parzen Windows, K-NN)
• Batch Perceptron
• SVM

Project 3

• Euclidean - Cosine Metrics
• Silhouette Coefficient - Rand Index
• Clustering (K-Means, Hierarchical)
• Dimensionality Reduction (PCA, LDA, MDS)

Project 4

• Neural Networks
• Autoencoders
• Decision Trees - Random Forest

Final Project

Image Classification (Face Mask - No Face Mask) -> CNN

Binding of chemical molecules to biological receptors (Binding - Not Binding) -> Random Forest - Gradient Boosting (XGBoost) - Adaptive Boosting (AdaBoost)