The aggregation of models like this isn't new, but simple layout of models available is useful. I can imagine being able to filter by model origin (OpenAI/Facebook/Google/etc), origin date (year), compared use case (why should I use VGG vs RNN).
Overall, great for people who are and aren't deeply immersed in ML.
Thanks! You hit the nail right on the head there, while aggregation is nothing new, we're hoping that the notebooks and tutorials provide an entrypoint into being able to get up and running with the model more quickly.
We're actually hoping to build ModelDepot into a place where anybody can share (well documented) models, and be able to discover the right ones for their needs.
The aggregation of models like this isn't new, but simple layout of models available is useful. I can imagine being able to filter by model origin (OpenAI/Facebook/Google/etc), origin date (year), compared use case (why should I use VGG vs RNN).
Overall, great for people who are and aren't deeply immersed in ML.