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: 11 days 6 hours 37 minutes
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Adversarial Explanations
Walt Woods joins us to discuss his paper with co-authors Jack Chen and Christof Teuscher.
ObjectNet
joins us to discuss - a new kind of vision dataset. In contrast to ImageNet, ObjectNet seeks to provide images that are more representative of the types of images an autonomous machine is likely to encounter in the real world....
Visualization and Interpretability
joins us to discuss how data visualization can be used to help make machine learning more interpretable and explainable. Find out more about Enrico at . More from Enrico with co-host Moritz Stefaner on the podcast!
Fooling Computer Vision
joins us to talk about a project in which specially designed printed images can fool a computer vision system, preventing it from identifying a person. Their attack targets the popular YOLO2 pre-trained image recognition model, and thus, is...
Interpretability
Interpretability Machine learning has shown a rapid expansion into every sector and industry. With increasing reliance on models and increasing stakes for the decisions of models, questions of how models actually work are becoming increasingly...
The Limits of NLP
We are joined by Colin Raffel to discuss the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer".