539 episodes

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.

Data Skeptic Kyle Polich

    • Technology
    • 4.5 • 60 Ratings

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.

    Generating 3D Animals with YouDream

    Generating 3D Animals with YouDream

    Generative AI can struggle to create realistic animals and 2D representations often have mistakes like extra limbs and tails. If 2D wasn’t hard enough, there are researchers working on generative 3D models. 3D models present an extra challenge because there is paucity of training datasets.In this episode, PhD students Sandeep and Oindrila walked us through their work on creating 3D animals using 2D data. Join us to learn about their pipelines, quality control, tie in with iNaturalist, and how this tech could streamline FX pipelines.

    • 1 hr
    Weird Communication

    Weird Communication

    Today, we sat down with Dr. Ignacio Escalante Meza to learn about opiliones and treehoppers. Opiliones, known as “daddy long legs” in the US, are understudied arachnids known for their tenacious locomotor behavior, sociality, and chemical communication. Treehoppers communicate through the stems of plants using vibrations. They can signal danger, attract mates, and communicate with their offspring. Join us to learn how researchers turn their vibrations into sound waves and study what they have to say.

    • 38 min
    Reducing the Impact of Ship Noise on Marine Mammals

    Reducing the Impact of Ship Noise on Marine Mammals

    Human shipping operations have increased significantly in the past few decades.  While that means international trade and cheap goods for humans, it also means the ocean has experienced an increase in noise pollution.  This has a measurable negative impact on marine mammals and other aquatic life.  Could mathematics be the solution?  This interview explores how optimization techniques can guide voyage optimization in a way that handles multiple optimization objectives including fuel cost and sound reduction.

    • 36 min
    Analysis of Unstructured Data

    Analysis of Unstructured Data

    Robbie Moon from the Georgia Tech Scheller College of Business joins us to discuss the analysis of unstructured data and the application of NLP methodologies towards financial data.

    • 27 min
    iNaturalist

    iNaturalist

    Have you ever participated in citizen science? Do you want to? One of the most popular platforms for crowdsourcing biodiversity data is iNaturalist. In addition to being a great science tool, the iNaturalist app can help you identify the organisms you encounter every day. We talked to Executive Director Scott Laurie about how scientists use iNaturalist. We also got to discuss what makes iNaturalist’s AI species recognition so good, and how citizen scientists are constantly providing high-quality training data. Listen in and learn how this fun-to-use tool works, where it's headed, and how you can get involved.

    • 37 min
    Learn to Code

    Learn to Code

    Do you code or are you interested in learning to code? Join us today and hear from three individuals that are at very different stages of their coding journeys. Becky Hansis-O’Neill (also our co-host this season) shares her experiences as a newbie who wants to learn more. Dr. Malia Gehan, a self-taught developer interested in studying plant phenotypes, explains why and how she and her colleagues learned to code and developed PlantCV. Finally, Dr. John Wilmes discusses his work as a professional mathematician and Machine Learning Research Engineer. Whether you are thinking about learning to code or an expert, we’re sure you will see a bit of yourself in this episode. 

    • 49 min

Customer Reviews

4.5 out of 5
60 Ratings

60 Ratings

K800Dave ,

Crypto entertainment

I found the show as a result of a google search, I started listening as a way of building on my developing interest in data science and my hope to learn more about deep learning.

Generally I find that podcasts assume the listener has been there from the beginning and so to make sure I didn’t miss out on any important topics, I found the first episode and started listening.

At the point of writing this review, I’m still working my way through the back catalogue, I’m somewhere in 2015, in fact my review title is based on the crypto zoology episode which was pure entertainment.

Kyle, Lin Da and Yoshi are fantastic hosts. I’ve definitely learned a few things so far, I especially like the bigger sized mini episodes that explain really cool things like k-means clustering in really simple ways, just enough to give you an understanding and help you go off and do a bit more work on your own.

One thing to be aware of, with both Kyle and several of his guests, you will find many references to really great books, I’m spending a small fortune on reading material as a result 😁

Really enjoy the show, the format and the hosts. Highly recommended!

Iain W UK Twist Fan ,

Incredulous

What's the sentiment ? I got a pointer for this podcast
from a data scientist in London. The only Podcast I rate
anywhere near this level is TWIST. I can't belive it's free !

Neenbeans ,

Love this show

I am getting into data science and I really like the way this show tackles topics in ML and stats. I absolutely loved the Library Problem show because it was so cool to see a real life example worked all the way though and hear about how a data scientist might decide what to use (all these methods and ideas we'd heard about in pervious shows). If it's not giving away too many of your interview secrets, I'd love to hear more like the Library Problem.

This is an excellent show for anyone wanting to learn more about data science.

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