Data Skeptic

Un pódcast de Kyle Polich

Categorías:

553 Episodo

  1. Self-Explaining AI

    Publicado: 2/5/2020
  2. Plastic Bag Bans

    Publicado: 24/4/2020
  3. Self Driving Cars and Pedestrians

    Publicado: 18/4/2020
  4. Computer Vision is Not Perfect

    Publicado: 10/4/2020
  5. Uncertainty Representations

    Publicado: 4/4/2020
  6. AlphaGo, COVID-19 Contact Tracing and New Data Set

    Publicado: 28/3/2020
  7. Visualizing Uncertainty

    Publicado: 20/3/2020
  8. Interpretability Tooling

    Publicado: 13/3/2020
  9. Shapley Values

    Publicado: 6/3/2020
  10. Anchors as Explanations

    Publicado: 28/2/2020
  11. Mathematical Models of Ecological Systems

    Publicado: 22/2/2020
  12. Adversarial Explanations

    Publicado: 14/2/2020
  13. ObjectNet

    Publicado: 7/2/2020
  14. Visualization and Interpretability

    Publicado: 31/1/2020
  15. Interpretable One Shot Learning

    Publicado: 26/1/2020
  16. Fooling Computer Vision

    Publicado: 22/1/2020
  17. Algorithmic Fairness

    Publicado: 14/1/2020
  18. Interpretability

    Publicado: 7/1/2020
  19. NLP in 2019

    Publicado: 31/12/2019
  20. The Limits of NLP

    Publicado: 24/12/2019

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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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