530 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 • 480 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.

    HMMs for Behavior

    HMMs for Behavior

    Théo Michelot has made a career out of tackling tough ecological questions using time-series data. How do scientists turn a series of GPS location observations over time into useful behavioral data? GPS tech has improved to the point that modern data sets are large and complex. In this episode, Théo takes us through his research and the application of Hidden Markov Models to complex time series data. If you have ever wondered what biologists do with data from those GPS collars you have seen on TV, this is the episode for you! 

    • 45 min
    Bioinspired Engineering

    Bioinspired Engineering

    Brian Taylor shares his research on magnetoreception. Animals like birds and sea turtles use magnetoreception to use the Earth’s magnetic field for navigation, but it’s not a sense that’s well understood. Brian uses animal magnetoreception to engineer new ways to navigate the globe. Even cooler, he also takes hypotheses for how magnetoreception works in animals and uses computational simulations to digitally test them. Check out this episode to hear more about Brian’s research and learn more about this little known sensory ability. 

    • 38 min
    Modelling Evolution

    Modelling Evolution

    Modeling evolutionary processes goes way beyond the Hardy-Weinberg Equilibrium we all learned in biology class. Natural selection comes from many sources like resources availability, mate preferences, competition. Modeling entire populations of organisms of different species is the holy grail of digital evolution. Join our discussion with evolutionary biologist and software engineer Ben Haller to learn about his work on SLiM and how it helps other biologists model population genetics over time. 

    • 41 min
    Behavioral Genetics

    Behavioral Genetics

    It’s almost impossible to think about animal behavior without thinking of dogs! Our canine friends are a subspecies of wolf that has been co-evolving with us for tens of thousands of years. The transition from wolf to pet has required intense natural and artificial selection for behaviors that allow dogs to live alongside humans, but behavior is not so simple. Join us for a discussion with Dr. Jessica Hekman and learn about dog welfare, behavioral genetics, and the quest to understand the dogs in our lives. 

    • 47 min
    Signal in the Noise

    Signal in the Noise

    In this episode, we are joined by Barbara Webb and Anna Hadjitofi. Barbara runs the Insect Robotics lab at the University of Edinburgh, and Anna is a PhD student at the School of Informatics at the university. She is interested in studying and understanding the neural mechanism of the honeybee waggle dance. They join us to discuss the paper: Dynamic antennal positioning allows honeybee followers to decode the dance.

    • 41 min
    Pose Tracking

    Pose Tracking

    Many researchers and students have painstakingly labeled precise details about the body positions of the creatures they study. Can AI be used for this labeling? Of course it can! Today's episode discusses Social LEAP Estimates Animal Poses (SLEAP), a software solution to train AI to perform this tedious but important labeling work.

    • 50 min

Customer Reviews

4.5 out of 5
480 Ratings

480 Ratings

calzone.onsets ,

Great resource

A colleague introduced me to Data Skeptic last year and I’ve been enjoying the episodes. Kyle’s good at covering topics from many levels of data science understanding—his mini series with a non-data scientist are a great way to learn the basics!

joey...1989 ,

Data science

Lots of interviews

Steveo CO ,

Amazing

I have been following for a few months now. If you’re looking for a wide perspective on big data and AI, this is the place. Kyle has a wide knowledge base, he’s not focused on a simple thing, rather, he explores multiple models, to help with research. His guests are amazing. I can’t wait to be invited to appear on the show to discuss standard operations for an average guy doing signs and lighting.

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