Mean-Square-Error InferenceCovers the concept of mean-square-error inference and optimal estimators for inference problems using different design criteria.
Linear Regression BasicsCovers the basics of linear regression in machine learning, including model training, loss functions, and evaluation metrics.
Real Estate Market TrendsExplores the evolution of real estate prices, hedonic models, and the UBS Swiss Real Estate Bubble Index.
Sampling strategiesExplores sampling strategies for signals, emphasizing the importance of controlling errors in the sampling process.
Model Selection in StatisticsExplores model selection in statistics, discussing principles, probabilistic models, characteristics evaluation, and data visualization methods.
Detection & EstimationCovers the fundamentals of detection and estimation theory, focusing on mean-squared error and hypothesis testing.