Data Skeptic

A podcast by Kyle Polich

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549 Episodes

  1. Do We Need Deep Learning in Time Series

    Published: 16/06/2021
  2. Detecting Drift

    Published: 11/06/2021
  3. Darts Library for Time Series

    Published: 31/05/2021
  4. Forecasting Principles and Practice

    Published: 24/05/2021
  5. Prequisites for Time Series

    Published: 21/05/2021
  6. Orders of Magnitude

    Published: 7/05/2021
  7. They're Coming for Our Jobs

    Published: 3/05/2021
  8. Pandemic Machine Learning Pitfalls

    Published: 26/04/2021
  9. Flesch Kincaid Readability Tests

    Published: 19/04/2021
  10. Fairness Aware Outlier Detection

    Published: 9/04/2021
  11. Life May be Rare

    Published: 5/04/2021
  12. Social Networks

    Published: 29/03/2021
  13. The QAnon Conspiracy

    Published: 22/03/2021
  14. Benchmarking Vision on Edge vs Cloud

    Published: 15/03/2021
  15. Goodhart's Law in Reinforcement Learning

    Published: 5/03/2021
  16. Video Anomaly Detection

    Published: 1/03/2021
  17. Fault Tolerant Distributed Gradient Descent

    Published: 22/02/2021
  18. Decentralized Information Gathering

    Published: 15/02/2021
  19. Leaderless Consensus

    Published: 5/02/2021
  20. Automatic Summarization

    Published: 29/01/2021

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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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