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.
https://dataskeptic.com
Gesamtlänge aller Episoden: 7 days 6 hours 51 minutes
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Predicting Urban Land Use
Today on the show we have Daniel Omeiza, a doctoral student in the computer science department of the University of Oxford, who joins us to talk about his work Efficient Machine Learning for Large-Scale Urban Land-Use Forecasting in Sub-Saharan Africa.
Opportunities for Skillful Weather Prediction
Today on the show we have Elizabeth Barnes, Associate Professor in the department of Atmospheric Science at Colorado State University, who joins us to talk about her work Identifying Opportunities for Skillful Weather Prediction with Interpretable...
Predicting Stock Prices
Today on the show we have Andrea Fronzetti Colladon (@iandreafc), currently working at the University of Perugia and inventor of the Semantic Brand Score, joins us to talk about his work studying human communication and social interaction. We discuss...
N-Beats
Today on the show we have Boris Oreshkin @boreshkin, a Senior Research Scientist at Unity Technologies, who joins us today to talk about his work N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting. Works Mentioned:...
Translation Automation
Today we are back with another episode discussing AI in the work field. AI has, is, and will continue to facilitate the automation of work done by humans. Sometimes this may be an entire role. Other times it may automate a particular part of their...
Time Series at the Beach
Shane Ross, Professor of Aerospace and Ocean Engineering at Virginia Tech University, comes on today to talk about his work “Beach-level 24-hour forecasts of Florida red tide-induced respiratory irritation.”
Automatic Identification of Outlier Galaxy Images
Lior Shamir, Associate Professor of Computer Science at Kansas University, joins us today to talk about the recent paper Automatic Identification of Outliers in Hubble Space Telescope Galaxy Images. Follow Lio on Twitter @shamir_lior
Do We Need Deep Learning in Time Series
Shereen Elsayed and Daniela Thyssens, both are PhD Student at Hildesheim University in Germany, come on today to talk about the work “Do We Really Need Deep Learning Models for Time Series Forecasting?”
Detecting Drift
Sam Ackerman, Research Data Scientist at IBM Research Labs in Haifa, Israel, joins us today to talk about his work Detection of Data Drift and Outliers Affecting Machine Learning Model Performance Over Time. Check out Sam's IBM statistics/ML blog at: ...
Darts Library for Time Series
Julien Herzen, PhD graduate from EPFL in Switzerland, comes on today to talk about his work with Unit 8 and the development of the Python Library: Darts.