Data Clustering

Data Clustering

This lecture overviews Data Clustering  that has many applications in e.g., facial image clustering, signal/image clustering, concept creation.  It covers the following topics in detail: Clustering Definitions. Distance measures, Mahalanobis distance, Euclidean distance, Lp norm, L1 Norm  Similarity measures, Cosine similarity, Correlation coefficient. Distance Functions between a Point and a Set. Distance Functions between two… Continue reading Data Clustering

Distance-based Classification

This lecture overviews Distance-based Classification that has many applications in classification. It covers the following topics in detail: k-Nearest neighbor classification, Nearest neighbor graphs Supervised Learning Vector Quantization, LVQ1/2/3.

Introduction to Machine Learning

This lecture will cover the basic concepts of Machine Learning to alleviate inconsistencies towards concept and notation accuracy. Supervised, self-supervised, unsupervised, semi-supervised learning. Multi-task Machine Learning. Classification, regression. Object detection, Object tracking. Clustering. Dimensionality reduction, data retrieval. Artificial Neural Networks. Adversarial Machine Learning. Generative Machine Learning. Temporal Machine learning (Recurrent Neural Networks). Continual Learning (few-shot… Continue reading Introduction to Machine Learning

Agent Systems

This lecture overviews Agent Systems that has many applications in multi-party behavior modeling. It covers the following topics in detail: Intelligent Agents, Competitive Multi-Agent Systems, Nash Equilibrium, Simulation tools (NetLogo, MASON, AnyLogic,Altreva) and Applications.

Natural Selection

This lecture overviews Natural Selection simulation that has many applications in ecology and sociology studies. It covers the following topics in detail: Introduction to Natural Selection, Simulation of a Natural Selection in a Society, Rules of the Society, Simulation results.