Linear Algebra in Data ScienceExplores the application of linear algebra in data science, covering variance reduction, model distribution theory, and maximum likelihood estimates.
Maximum Likelihood EstimationCovers Maximum Likelihood Estimation, focusing on ML Estimation-Distribution, Shrinkage Estimation, and Loss functions.
Compression: PredictionCovers the concepts of compression and prediction using prefix-free codes and distributions.
Parameter EstimationDiscusses parameter estimation, including checks, quality, distribution, and statistical properties of estimates.