Saw the plug in R/datascience I subscribed after watching this video. Love it! Like someone else mentioned the current channel name gets swamped by Stanford University in the algo. Cheers
Thank you for the subscription! yes the Stanford Uni is crushing my SEO. I'm thinking about the name change as we speak and will do an updated vid soon. Thanks!
Actually, I don't know if you do a video on this, but the biggest challenge I have with Bayesian Statistics is not that I have too little but too much data which makes MCMC slow. I've been trying to use the following to solve this problem, use aggregated data in modelling (Binom Likelihoods for instance), sample more wisely so that not every strata has 10,000 observersations, Think about using variational inference, take smaller samples from my posterior since my models aren't super complicated. What do you think about that? My biggest fear with Bayesian stats is creating models that take too long to run, not having too little data!
