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Data Skeptic

Author: Kyle Polich

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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.
275 Episodes
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Catastrophic Forgetting

Catastrophic Forgetting

2019-07-1500:21:271

Kyle and Linhda discuss some high level theory of mind and overview the concept machine learning concept of catastrophic forgetting.
Transfer Learning

Transfer Learning

2019-07-0800:29:511

Sebastian Ruder is a research scientist at DeepMind.  In this episode, he joins us to discuss the state of the art in transfer learning and his contributions to it.
In 2017, Facebook published a paper called Deal or No Deal? End-to-End Learning for Negotiation Dialogues. In this research, the reinforcement learning agents developed a mechanism of communication (which could be called a language) that made them able to optimize their scores in the negotiation game. Many media sources reported this as if it were a first step towards Skynet taking over. In this episode, Kyle discusses bargaining agents and the actual results of this research.
Under Resourced Languages

Under Resourced Languages

2019-06-1500:16:46

Priyanka Biswas joins us in this episode to discuss natural language processing for languages that do not have as many resources as those that are more commonly studied such as English.  Successful NLP projects benefit from the availability of like large corpora, well-annotated corpora, software libraries, and pre-trained models.  For languages that researchers have not paid as much attention to, these tools are not always available.
Named Entity Recognition

Named Entity Recognition

2019-06-0800:17:121

Kyle and Linh Da discuss the class of approaches called "Named Entity Recognition" or NER.  NER algorithms take any string as input and return a list of "entities" - specific facts and agents in the text along with a classification of the type (e.g. person, date, place).
The Death of a Language

The Death of a Language

2019-06-0100:20:192

USC students from the CAIS++ student organization have created a variety of novel projects under the mission statement of "artificial intelligence for social good". In this episode, Kyle interviews Zane and Leena about the Endangered Languages Project.
Neural Turing Machines

Neural Turing Machines

2019-05-2500:25:274

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

NCAA Predictions on Spark

2019-05-1100:23:53

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

The Transformer

2019-05-0300:15:23

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.
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Comments (8)

Akshay Shirsath

Thoughtful episode.

Jun 8th
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Sindhuja Rao

Akshay Shirsath interesting

Jun 8th
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Achint Verma

A very very high level introduction to Kalman Filters. You could have talked about the matrices.

Mar 29th
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Troy Kirin

Golden, thanks for this!

Mar 19th
Reply

Vannucci Santos

Why the guy talking about ethics was so evasive?

Dec 25th
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Anna Malahova

I love everything about this podcast channel! It is easy to listen to, easy to understand without data science background, interesting topics and examples of situations where to apply. Very enjoyable and entertaining delivery. Informative show notes that help you to recall what the episode was about even after a while. Really can't think about any downsides. I am listening to all episodes starting from early days like an audiobook, love how music into evolved over time.

Nov 24th
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Abdul Wahab Abrar

What about using Deep Learning techniques directly and integrate it with Neuroscience

Feb 12th
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Giancarlo Vercellino

rilevante dal 23esimo minuto

Dec 12th
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