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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.

info_outline Data Ethics 12/07/2018
info_outline Escaping the Rabbit Hole 11/30/2018
info_outline Theorem Provers 11/23/2018
info_outline Automated Fact Checking 11/16/2018
info_outline Single Source of Truth 11/09/2018
info_outline Detecting Fast Radio Bursts with Deep Learning 11/02/2018
info_outline Being Bayesian 10/26/2018
info_outline Modeling Fake News 10/19/2018
info_outline The Louvain Method for Community Detection 10/12/2018
info_outline Cultural Cognition of Scientific Consensus 10/05/2018
info_outline False Discovery Rates 09/28/2018
info_outline Deep Fakes 09/21/2018
info_outline Fake News Midterm 09/14/2018
info_outline Quality Score 09/07/2018
info_outline The Knowledge Illusion 08/31/2018
info_outline Click Through Rates 08/24/2018
info_outline Algorithmic Detection of Fake News 08/17/2018
info_outline Ant Intelligence 08/10/2018
info_outline Human Detection of Fake News 08/03/2018
info_outline Spam Filtering with Naive Bayes 07/27/2018
info_outline The Spread of Fake News 07/20/2018
info_outline Fake News 07/13/2018
info_outline Dev Ops for Data Science 07/11/2018
info_outline First Order Logic 07/06/2018
info_outline Blind Spots in Reinforcement Learning 06/29/2018
info_outline Defending Against Adversarial Attacks 06/22/2018
info_outline Transfer Learning 06/15/2018
info_outline Medical Imaging Training Techniques 06/08/2018
info_outline Kalman Filters 06/01/2018
info_outline AI in Industry 05/25/2018