Data Skeptic

A podcast by Kyle Polich

Categories:

549 Episodes

  1. Uncertainty Representations

    Published: 4/04/2020
  2. AlphaGo, COVID-19 Contact Tracing and New Data Set

    Published: 28/03/2020
  3. Visualizing Uncertainty

    Published: 20/03/2020
  4. Interpretability Tooling

    Published: 13/03/2020
  5. Shapley Values

    Published: 6/03/2020
  6. Anchors as Explanations

    Published: 28/02/2020
  7. Mathematical Models of Ecological Systems

    Published: 22/02/2020
  8. Adversarial Explanations

    Published: 14/02/2020
  9. ObjectNet

    Published: 7/02/2020
  10. Visualization and Interpretability

    Published: 31/01/2020
  11. Interpretable One Shot Learning

    Published: 26/01/2020
  12. Fooling Computer Vision

    Published: 22/01/2020
  13. Algorithmic Fairness

    Published: 14/01/2020
  14. Interpretability

    Published: 7/01/2020
  15. NLP in 2019

    Published: 31/12/2019
  16. The Limits of NLP

    Published: 24/12/2019
  17. Jumpstart Your ML Project

    Published: 15/12/2019
  18. Serverless NLP Model Training

    Published: 10/12/2019
  19. Team Data Science Process

    Published: 3/12/2019
  20. Ancient Text Restoration

    Published: 1/12/2019

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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.

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