The examples are there to provide interesting implementations, tutorials, and/or articles as easy entries. I'd say some of them might look little dull to experienced veterans.
Nonetheless, they are valuable for those who seek to indulge into the fields. Hope you can look at them in that angle.
So I’m very far from experienced or a veteran in this field. Perhaps I didn’t word it properly - the github repo literally had no ML code at all. It was a todo.
In general, it’s a great resource. The field moves so fast it’s nice to have a no-BS list of things to peruse once a week. The SNR of twitter has gotten so bad, I could replace it with something like a weekly update.
Ah, actually, the author's github repository has notebook, data, and additional tutorials. It's just that he did not link them in README.md. For example, you can see "Beginner MNIST" here ( https://github.com/Andrewnetwork/WorkshopScipy/blob/master/N... ) Since every collected project is periodically updated, the links in README.md might work sometime later.
I'm usually very careful when selecting a project, and his project gave me a hesitant moment. But, I thought the amount of material gone into building the project would outweigh inconvenience. I think I was short-sighted there. I'll make a note on this, and try to make clear communication with author in the future.
In terms of performance per cost, the cluster isn't on par with x86 system. Probably, not even close. Nonetheless, the network cost is real, and you get to have a first hand experience of how your algorithm performs.
It only serves two fronts; education and development.
Education-wise, you need something dirt-cheap to play with. For developer, you need some intermediate stage to deploy your work to test before going after a big cluster.
I've never imagined the RPI cluster to be taken seriously for production purpose. It only serves two purposes; education and developmental staging. For those two, you have a real hardware cluster that serves you superbly showing every nature you can experience with big-ass datacenter cluster.
