News Recommendations
News recommendation algorithms influence far more than what stories we click—they can shape our understanding of the world. In this episode,...
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Religion & Spirituality
Data Skeptic
Data Skeptic is a data science podcast exploring machine learning, statistics, artificial intelligence, and other data topics through short tutorials and interviews with domain experts.
Data Skeptic Podcast Guide
Listen to Data Skeptic, a Religion & Spirituality podcast by Kyle Polich. Stream 604 episodes in English, follow new audio stories, and play episodes online on Radio and Podcast.
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Episodes
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Give Users the Wheel
What if you could simply tell a recommendation system what you want instead of relying on likes, dislikes, and watch history? Kyle Polich ta...
AutoLike
How can researchers audit recommendation systems when the algorithms are hidden from view? Hieu Le joins Kyle Polich to discuss Auto-Like, a...
Student Spotlight: Aaron Payne, Data Analyst
Aaron Payne, an MBA student at Georgia Tech studying business analytics and a Senior Insights Analyst at Chick-fil-A, joins Kyle Polich to t...
The Future is Agentic in Recommender Systems
Kyle Polich sits down with Yashar Deldjoo, research scientist and Associate Professor at the Polytechnic University of Bari, to explore how...
Book Ratings and Recommendations
Goodreads star ratings can be misleading as measures of "book quality," and research from Hannes Rosenbusch suggests that for many professio...
Disentanglement and Interpretability in Recommender Systems
Ervin Dervishaj, a PhD student at the University of Copenhagen, discusses his research on disentangled representation learning in recommende...
Collective Altruism in Recommender Systems
Ekaterina (Kat) Fedorova from MIT EECS joins us to discuss strategic learning in recommender systems—what happens when users collectively co...
Niche vs Mainstream
Anas Buhayh discusses multi-stakeholder fairness in recommender systems and the S'mores framework—a simulation allowing users to choose betw...
Healthy Friction in Job Recommender Systems
In this episode, host Kyle Polich speaks with Roan Schellingerhout, a fourth-year PhD student at Maastricht University, about explainable mu...
Fairness in PCA-Based Recommenders
In this episode, we explore the fascinating world of recommender systems and algorithmic fairness with David Liu, Assistant Research Profess...
Video Recommendations in Industry
In this episode, Kyle Polich sits down with Cory Zechmann , a content curator working in streaming television with 16 years of experience ru...
Eye Tracking in Recommender Systems
In this episode, Santiago de Leon takes us deep into the world of eye tracking and its revolutionary applications in recommender systems. As...
Cracking the Cold Start Problem
In this episode of Data Skeptic, we dive deep into the technical foundations of building modern recommender systems. Unlike traditional mach...
Designing Recommender Systems for Digital Humanities
In this episode of Data Skeptic, we explore the fascinating intersection of recommender systems and digital humanities with guest Florian At...
DataRec Library for Reproducible in Recommend Systems
In this episode of Data Skeptic's Recommender Systems series, host Kyle Polich explores DataRec, a new Python library designed to bring repr...
Shilling Attacks on Recommender Systems
In this episode of Data Skeptic's Recommender Systems series, Kyle sits down with Aditya Chichani, a senior machine learning engineer at Wal...
Music Playlist Recommendations
In this episode, Rebecca Salganik , a PhD student at the University of Rochester with a background in vocal performance and composition, dis...
Bypassing the Popularity Bias
Data Skeptic is a data science podcast exploring machine learning, statistics, artificial intelligence, and other data topics through short...
Sustainable Recommender Systems for Tourism
In this episode, we speak with Ashmi Banerjee, a doctoral candidate at the Technical University of Munich, about her pioneering research on...