Hi. Hit me up and I'll set you up so you could have an environment that already has pretty much all the libraries installed, where you can track experiments, deploy and invoke models, schedule long running notebooks, collaborate in near real-time on notebooks, have multiple check-points, and automatically parametrize notebooks so you run experiments filling up a form.
It's a play version of our internal tool to which we invited around thirty students of one of our colleagues for their ML projects.
This way you can concentrate on the actual courses instead of the nightmare of setting things up and the usual ML specific problems. This should speed up your progress, because people lose an ungodly amount of time on these issues. Well, maybe not on course projects, but in real projects they do. I'll also add you to the Slack workspace in case you encounter issues.
It's a play version of our internal tool to which we invited around thirty students of one of our colleagues for their ML projects.
This way you can concentrate on the actual courses instead of the nightmare of setting things up and the usual ML specific problems. This should speed up your progress, because people lose an ungodly amount of time on these issues. Well, maybe not on course projects, but in real projects they do. I'll also add you to the Slack workspace in case you encounter issues.