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#56 Causal & Probabilistic Machine Learning, with Robert Osazuwa Ness

Learning Bayesian Statistics

CHAPTER

Is Causal Inference the Most Helpful?

A lot of causal inference, it developes by looking at ways of saying some causal thing that you wont estimate. Instead of doing all these estimation techniques, what i'm going to do is just create a generative model which represents my generating process. And since maybe i don't observe everything, there's going to be some latent variables in that model. But if all you want is to estimate one query, and you can just say, like worms, you know, theoretically all i have to do is regress this on this, and then get the estimater of choice. We should not always use that. Then am curious what would be the circumstances in which causal, generative matine learning

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