Data Skeptic

Un podcast de Kyle Polich

Catégories:

549 Épisodes

  1. Uncertainty Representations

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

    Publié: 28/03/2020
  3. Visualizing Uncertainty

    Publié: 20/03/2020
  4. Interpretability Tooling

    Publié: 13/03/2020
  5. Shapley Values

    Publié: 06/03/2020
  6. Anchors as Explanations

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

    Publié: 22/02/2020
  8. Adversarial Explanations

    Publié: 14/02/2020
  9. ObjectNet

    Publié: 07/02/2020
  10. Visualization and Interpretability

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

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

    Publié: 22/01/2020
  13. Algorithmic Fairness

    Publié: 14/01/2020
  14. Interpretability

    Publié: 07/01/2020
  15. NLP in 2019

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

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

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

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

    Publié: 03/12/2019
  20. Ancient Text Restoration

    Publié: 01/12/2019

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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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