Built with pytorch backend Usually involves specifying a generative process Usually either use Stochastic Variational Inference (SVI) optimization methods or Monte Carlo Markov Chain (MCMC) sampling methods For SVI Define a model and a guide (variational distribution) guides define where the parameters are to be learnt Example model and guide code
def reverseList(self, head: ListNode) -> ListNode: current = head while (current and current.next): next = current.next current.next = next.next next.next = head head = next return head This is a real basic problem, but it can be tricky.
I’m going to add another level of granularity to the notes of my website: Zettelkasten.
I think there’s a strong case this will improve my learning and production.
Blog posts are polished, well-researched, peer-reviewed pieces that take 15-20 hours to write.