エピソード

  • Generative Adversarial Networks (GANs) Explained: From DL Basics to Real-World Training Tips

    Generative Adversarial Networks (GANs) Explained: From DL Basics to Real-World Training Tips
    2025/06/10

    This episode breaks down how GANs work by starting with deep learning basics like CNNs, gradient descent, and regularization. We then get into what actually goes wrong when training these models and how to deal with it. It’s practical, straightforward, and meant for anyone trying to make sense of GANs in the real world.
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    28 分
  • Bayesian vs. Frequentist Thinking in Marketing Mix Modeling

    Bayesian vs. Frequentist Thinking in Marketing Mix Modeling
    2025/05/27

    In this episode, we unpack how Bayesian and Frequentist statistical approaches tackle marketing performance analysis, focusing on Marketing Mix Modeling (MMM). You’ll learn the key differences in interpretation, how Bayesian methods enable sequential updates and uncertainty modeling, and why they’re gaining traction in modern marketing analytics. Ideal for marketers, data scientists, and anyone curious about the “why” behind the math.
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    23 分