This is the 4th in a series of panel discussions in collaboration with Neuromatch Academy, the online computational neuroscience summer school. This is the first of 3 in the deep learning series. In this episode, the panelists discuss their experiences with some basics in deep learning, including Linear deep learning, Pytorch, multi-layer-perceptrons, optimization, & regularization.
Announcement: I'm releasing my Neuro-AI course April 10-13, after which it will be closed for some time. Learn more here. Support the show to...
Sanjeev and I discuss some of the progress toward understanding how deep learning works, specially under previous assumptions it wouldn’t or shouldn’t work as...
Support the Show Talia and I discuss her work on how our visual system is organized topographically, and divides into three main categories: big...