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.

https://dataskeptic.com

Eine durchschnittliche Folge dieses Podcasts dauert 25m. Bisher sind 301 Folge(n) erschienen. Jede Woche gibt es eine neue Folge dieses Podcasts
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ML Ops


Kyle met up with Damian Brady at MS Ignite 2019 to discuss machine learning operations.


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 2019-11-27  36m
 
 

Annotator Bias


The modern deep learning approaches to natural language processing are voracious in their demands for large corpora to train on.  Folk wisdom estimates used to be around 100k documents were required for effective training.  The availability...


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 2019-11-23  25m
 
 

Annotator Bias


The modern deep learning approaches to natural language processing are voracious in their demands for large corpora to train on.  Folk wisdom estimates used to be around 100k documents were required for effective training.  The availability...


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 2019-11-23  26m
 
 

NLP for Developers


While at MS Build 2019, Kyle sat down with Lance Olson from the Applied AI team about how tools like cognitive services and cognitive search enable non-data scientists to access relatively advanced NLP tools out of box, and how more advanced data...


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 2019-11-20  29m
 
 

Indigenous American Language Research


Manuel Mager joins us to discuss natural language processing for low and under-resourced languages.  We discuss current work in this area and the Naki Project which aggregates research on NLP for native and indigenous languages of the American...


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 2019-11-13  22m
 
 

Talking to GPT-2


GPT-2 is yet another in a succession of models like ELMo and BERT which adopt a similar deep learning architecture and train an unsupervised model on a massive text corpus. As we have been covering recently, these approaches are showing tremendous...


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 2019-10-31  29m
 
 

Reproducing Deep Learning Models


Rajiv Shah attempted to reproduce an earthquake-predicting deep learning model.  His results exposed some issues with the model.  Kyle and Rajiv discuss the original paper and Rajiv's analysis.


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 2019-10-23  22m
 
 

What BERT is Not


Allyson Ettinger joins us to discuss her work in computational linguistics, specifically in exploring some of the ways in which the popular natural language processing approach BERT has limitations.


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 2019-10-14  27m
 
 

SpanBERT


Omer Levy joins us to discuss "SpanBERT: Improving Pre-training by Representing and Predicting Spans". https://arxiv.org/abs/1907.10529


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 2019-10-08  24m
 
 

BERT is Shallow


Tim Nivens joins us this week to discuss his work exploring the limits of what BERT can do on certain natural language tasks such as adversarial attacks, compositional learning, and systematic learning.


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 2019-09-23  20m