I scraped a massive corpus of guest participants' interviews and publications to build personas, used a multi-agent workflow to simulate debate engagements dozens of times, and clustered extracted arguments to build a "debate landscape" forecast.
Working through the variance of Ridge predictions, I noticed the connection between Ridge shrinkage and principal component analysis — and why an isotropic penalty on anisotropic data produces PCA's coordinate system.
Economists and mathematicians are taught regression completely differently. This series tries to bridge the gap between data intuition and geometric elegance.