643: A.I. for Medicine
Super Data Science: ML & AI Podcast with Jon Krohn
00:00
Is There an Easy Way to Explain a Loss Function?
In Bayesian statistics we have like priors. And so do you kind of have like that kind of prior information that you can provide to the model? So this is actually interesting and when we built our first versions of this, we built something which called our blooper. We then went on to test well what if we let the model predict the whole thing because it will find it easy to predict the main part. That's where we moved on to immune builder. The second version is more accurate. Even though we're asking it in inverted comm as a harder question. Now it might be because it has better control of the overall function because it's not set up like a prior here.
Transcript
Play full episode
