Data Skeptic

A podcast by Kyle Polich

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565 Episodes

  1. [MINI] Sudoku \in NP

    Published: 11/10/2017
  2. The Computational Complexity of Machine Learning

    Published: 11/3/2017
  3. [MINI] Turing Machines

    Published: 10/27/2017
  4. The Complexity of Learning Neural Networks

    Published: 10/20/2017
  5. [MINI] Big Oh Analysis

    Published: 10/13/2017
  6. Data science tools and other announcements from Ignite

    Published: 10/6/2017
  7. Generative AI for Content Creation

    Published: 9/29/2017
  8. [MINI] One Shot Learning

    Published: 9/22/2017
  9. Recommender Systems Live from FARCON 2017

    Published: 9/15/2017
  10. [MINI] Long Short Term Memory

    Published: 9/8/2017
  11. Zillow Zestimate

    Published: 9/1/2017
  12. Cardiologist Level Arrhythmia Detection with CNNs

    Published: 8/25/2017
  13. [MINI] Recurrent Neural Networks

    Published: 8/18/2017
  14. Project Common Voice

    Published: 8/11/2017
  15. [MINI] Bayesian Belief Networks

    Published: 8/4/2017
  16. pix2code

    Published: 7/28/2017
  17. [MINI] Conditional Independence

    Published: 7/21/2017
  18. Estimating Sheep Pain with Facial Recognition

    Published: 7/14/2017
  19. CosmosDB

    Published: 7/7/2017
  20. [MINI] The Vanishing Gradient

    Published: 6/30/2017

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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.