Data science, big data, artificial intelligence, machine learning… they’re all the rage. In this podcast, Jessi Cisewski-Kehe and Susan Wang, 2 statisticians, give you a perspective on what’s happening in the realm of all things data. Random bantering included.
#50: Extreme Classification: All You Need Is Some Hash (Functions)
In part 2 of this saga on extreme classification, we get into the weeds on how MACH is able to magically handle such massive classification problems. The title says it all -- hash functions are the magical ingredient. We provide a step-by-step view of how one might come up with the MACH algorithm from first principles.
17 Jan 2020
#49: Extreme Classification: Going at MACH Speed (Part 1)
In this episode, Dr. Derek Feng drops by to chat about a recent paper on a divide-and-conquer approach (Merged-Averaged Classifiers via Hashing) to massive classification problems. In part 1 (of 2 episodes), we describe the general problem solved by and strategy taken by MACH, wherein the original large classification problem is broken down into smaller-sized classification problems. Next week in the second episode, we talk about more technical details of how the division of labor works, and why it works.
14 Dec 2019
#48: Where Moneyball Meets Footy
We've long heard about the waves that statistics has made in baseball. But what about soccer? In this episode, we summarize a few applications of statistics in European football (or American soccer).
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