Explores the role of conditional probability in understanding events and Bayes' theorem, with examples in regression analysis and everyday scenarios, demonstrating how our biological tissue runs probabilistic machinery.
This article explains the PCA algorithm and its implementation in Python. It covers key concepts such as Dimensionality Reduction, eigenvectors, and eigenvalues. The tutorial aims to provide a solid understanding of the algorithm's inner workings and its application for dealing with high-dimensional data and the curse of dimensionality.
‘I’ve been to Bali too’ (and I will be going back): are terrorist shocks to Bali’s tourist arrivals permanent or transitory?,”
sub-populations that have different variabilities from others. Here "variability" could be quantified by the variance or any other measure of statistical dispersion
