Covers probabilistic retrieval models, evaluation metrics, query likelihood, user relevance feedback, and query expansion.
Covers Probabilistic Information Retrieval, modeling relevance as a probability, query expansion, and automatic thesaurus generation.
Explores the significance of System Modeling Languages like OPM, SysML, and Modelica in modern Systems Engineering.
Covers the concept of distribution estimation and the optimization of parameters using different estimators.
Introduces Discrete Choice Analysis, covering scale, depth, data collection, and statistical inference.
Covers jacamar data analysis, smoking data models, and challenges with log-linear models in visual impairment data.
Covers binary classification, hypothesis testing, likelihood ratio tests, and decision rules.
