Data Skeptic

The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.

Eine durchschnittliche Folge dieses Podcasts dauert 27m. Bisher sind 396 Folge(n) erschienen. Dieser Podcast erscheint wöchentlich.

Gesamtlänge aller Episoden: 7 days 16 hours 47 minutes


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Forecasting in Supply Chain

Mahdi Abolghasemi, Lecturer at Monash University, joins us today to talk about his work "Demand forecasting in supply chain: The impact of demand volatility in the presence of promotion."  



Black Friday

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Comparing Time Series with HCTSA

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Change Point Detection Algorithms

Gerrit van den Burg, Postdoctoral Researcher at The Alan Turing Institute, joins us today to discuss his work "An Evaluation of Change Point Detection Algorithms."



Time Series for Good

Bahman Rostami-Tabar, Senior Lecturer in Management Science at Cardiff University, joins us today to talk about his work "Forecasting and its Beneficiaries."


 2021-11-01  37m

Long Term Time Series Forecasting

Alex Mallen, Computer Science student at the University of Washington, and Henning Lange, a Postdoctoral Scholar in Applied Math at the University of Washington, join us today to share their work "Deep Probabilistic Koopman: Long-term Time-Series...


 2021-10-25  37m

Fast and Frugal Time Series Forecasting

Fotios Petropoulos, Professor of Management Science at the University of Bath in The U.K., joins us today to talk about his work "Fast and Frugal Time Series Forecasting."


 2021-10-17  37m

Causal Inference in Educational Systems

Manie Tadayon, a PhD graduate from the ECE department at University of California, Los Angeles, joins us today to talk about his work “Comparative Analysis of the Hidden Markov Model and LSTM: A Simulative Approach.”


 2021-10-11  41m

Boosted Embeddings for Time Series

Sankeerth Rao Karingula, ML Researcher at Palo Alto Networks, joins us today to talk about his work “Boosted Embeddings for Time Series Forecasting.” Works Mentioned by Sankeerth Rao Karingula, Nandini Ramanan, Rasool Tahmasbi, Mehrnaz Amjadi,...


 2021-10-04  28m