9 min listen
Recommender Systems Live from FARCON 2017
FromData Skeptic
ratings:
Length:
46 minutes
Released:
Sep 15, 2017
Format:
Podcast episode
Description
Recommender systems play an important role in providing personalized content to online users. Yet, typical data mining techniques are not well suited for the unique challenges that recommender systems face. In this episode, host Kyle Polich joins Dr. Joseph Konstan from the University of Minnesota at a live recording at FARCON 2017 in Minneapolis to discuss recommender systems and how machine learning can create better user experiences.
Released:
Sep 15, 2017
Format:
Podcast episode
Titles in the series (100)
[MINI] Anscombe's Quartet: This mini-episode discusses Anscombe's Quartet, a series of four datasets which are clearly very different but share some similar statistical properties with one another. For example, each of the four plots has the same mean and variance on both... by Data Skeptic