Data Skeptic

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Natural Sciences
**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.

Latest Episodes:

Neural Turing Machines May 25, 2019

Show notes

Kyle and Linh Da discuss the concepts behind the neural Turing machine.

Data Infrastructure in the Cloud May 18, 2019

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Kyle chats with Rohan Kumar about hyperscale, data at the edge, and a variety of other trends in data engineering in the cloud.

NCAA Predictions on Spark May 11, 2019

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In this episode, Kyle interviews Laura Edell at MS Build 2019. The conversation covers a number of topics, notably her NCAA Final 4 prediction model.

The Transformer May 03, 2019

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Kyle and Linhda discuss attention and the transformer - an encoder/decoder architecture that extends the basic ideas of vector embeddings like word2vec into a more contextual use case.

Mapping Dialects with Twitter Data Apr 26, 2019

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When users on Twitter post with geographic tags, it creates the opportunity for a variety of interesting questions to be posed having to do with language, dialects, and location. In this episode, Kyle interviews Bruno Gonçalves about his work studying language in this way.

Sentiment Analysis Apr 20, 2019

Show notes

This is an interview with Ellen Loeshelle, Director of Product Management at Clarabridge. We primarily discuss sentiment analysis.

Attention Primer Apr 13, 2019

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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.

Cross-lingual Short-text Matching Apr 05, 2019

Show notes

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 errors are a normal part of the conversation.

>>> Good mornink

>>> morning

Yet such short messages are also important for businesses whose users are unlikely to read a large block of text upon completing an order. Similarly, a business might want to offer assistance and effective question and answering solutions in an automated and ideally multi-lingual way. In this episode, we discuss techniques for designing solutions like that.

ELMo Mar 29, 2019

Show notes

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 space, out of box, proved to be incredibly useful in a wide variety of seemingly unrelated NLP tasks like sentiment analysis and name entity recognition.

BLEU Mar 23, 2019

Show notes

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 it the perfect measure of quality of machine translation?

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