Sampling strategiesExplores sampling strategies for signals, emphasizing the importance of controlling errors in the sampling process.
Detection & EstimationCovers the fundamentals of detection and estimation theory, focusing on mean-squared error and hypothesis testing.
Adaptive EqualizationExplores adaptive equalization in digital communication systems to compensate for channel distortion and track time-varying conditions.
Linear Regression BasicsCovers the basics of linear regression in machine learning, including model training, loss functions, and evaluation metrics.
Bayesian Inference: Part 2Explores Bayesian inference, multiclass classification, logistic regression, and linear regression inference.
