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 299 Folge(n) erschienen. Dies ist ein wöchentlich erscheinender Podcast
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Algorithmic Fairness


This episode includes an interview with Aaron Roth author of .


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   42m
 
 

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...


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   32m
 
 

NLP in 2019


A year in recap.


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   38m
 
 

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".


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   29m
 
 

Jumpstart Your ML Project


Seth Juarez joins us to discuss the toolbox of options available to a data scientist to jumpstart or extend their machine learning efforts.


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 2019-12-15  20m
 
 

Serverless NLP Model Training


Alex Reeves joins us to discuss some of the challenges around building a serverless, scalable, generic machine learning pipeline.  The is a technical deep dive on architecting solutions and a discussion of some of the design choices made.


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 2019-12-10  29m
 
 

Team Data Science Process


Buck Woody joins Kyle to share experiences from the field and the application of the Team Data Science Process - a popular six-phase workflow for doing data science.  


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 2019-12-03  41m
 
 

Ancient Text Restoration


Thea Sommerschield joins us this week to discuss the development of Pythia - a machine learning model trained to assist in the reconstruction of ancient language text.


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 2019-12-01  41m
 
 

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