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 24m. Bisher sind 284 Folge(n) erschienen. Dieser Podcast erscheint wöchentlich
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Attention Primer


A gentle introduction to the very high-level idea of "attention" in machine learning, as it will play a major role in some upcoming episodes over the next few weeks.


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 2019-04-13  14m
 
 

Cross-lingual Short-text Matching


Modern messaging technology has facilitated a trend towards highly compact, short messages send by users who can presume a great amount of context held between the communicating parties.  The rules of grammar may be discarded and often visible...


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 2019-04-05  24m
 
 

ELMo


ELMo (Embeddings from Language Models) introduced the idea of deep contextualized word representations. It extends previous ideas like word2vec and GloVe. The ELMo model is a neural network able to map natural language into a vector space. This vector...


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 2019-03-29  23m
 
 

BLEU


Bilingual evaluation understudy (or BLEU) is a metric for evaluating the quality of machine translation using human translation as examples of acceptable quality results. This metric has become a widely used standard in the research literature. But is...


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 2019-03-23  42m
 
 

Simultaneous Translation at Baidu


While at NeurIPS 2018, Kyle chatted with Liang Huang about his work with Baidu research on simultaneous translation, which was demoed at the conference.


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 2019-03-15  24m
 
 

Human vs Machine Transcription


Machine transcription (the process of translating audio recordings of language to text) has come a long way in recent years. But how do the errors made during machine transcription compare to the errors made by a human transcriber? Find out in this...


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 2019-03-08  32m
 
 

seq2seq


A sequence to sequence (or seq2seq) model is neural architecture used for translation (and other tasks) which consists of an encoder and a decoder. The encoder/decoder architecture has obvious promise for machine translation, and has been successfully...


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 2019-03-01  21m
 
 

Text Mining in R


Kyle interviews Julia Silge about her path into data science, her book Text Mining with R, and some of the ways in which she's used natural language processing in projects both personal and professional. Related Links ...


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 2019-02-22  20m
 
 

Recurrent Relational Networks


One of the most challenging NLP tasks is natural language understanding and reasoning. How can we construct algorithms that are able to achieve human level understanding of text and be able to answer general questions about it? This is truly an open...


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 2019-02-15  19m
 
 

Text World and Word Embedding Lower Bounds


In the first half of this episode, Kyle speaks with Marc-Alexandre Côté and Wendy Tay about Text World.  Text World is an engine that simulates text adventure games.  Developers are encouraged to try out their reinforcement learning skills...


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 2019-02-08  39m