Data Skeptic

A podcast by Kyle Polich

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571 Episodes

  1. Mercedes Benz Machine Learning Research

    Published: 14/12/2017
  2. [MINI] Parallel Algorithms

    Published: 8/12/2017
  3. Quantum Computing

    Published: 1/12/2017
  4. Azure Databricks

    Published: 28/11/2017
  5. [MINI] Exponential Time Algorithms

    Published: 24/11/2017
  6. P vs NP

    Published: 17/11/2017
  7. [MINI] Sudoku \in NP

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

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

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

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

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

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

    Published: 29/09/2017
  14. [MINI] One Shot Learning

    Published: 22/09/2017
  15. Recommender Systems Live from FARCON 2017

    Published: 15/09/2017
  16. [MINI] Long Short Term Memory

    Published: 8/09/2017
  17. Zillow Zestimate

    Published: 1/09/2017
  18. Cardiologist Level Arrhythmia Detection with CNNs

    Published: 25/08/2017
  19. [MINI] Recurrent Neural Networks

    Published: 18/08/2017
  20. Project Common Voice

    Published: 11/08/2017

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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.

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