Convex (and non-convex) Optimization - a podcast by Ben Jaffe and Katie Malone

Convex optimization is one of the keys to data science, both because some problems straight-up call for optimization solutions and because popular algorithms like a gradient descent solution to ordinary least squares are supported by optimization techniques. But there are all kinds of subtleties, starting with convex and non-convex functions, why gradient descent is really an optimization problem, and what that means for your average data scientist or statistician.

Further episodes of Linear Digressions

Further podcasts by Ben Jaffe and Katie Malone

Website of Ben Jaffe and Katie Malone