[iverjo]

This is nice :) Kudos to the Youtube guys for releasing this. I'm a data scientist in a startup where one of the things I do is create multi-label models for classifying YouTube videos. My current model has 90 % precision and 69 % recall, while Youtube-8M has 78 % precision and 14 % recall, with respect to the human raters. I guess one of the reasons is that my model only has around 100 categories, while Youtube-8M has 4800. It's like comparing apples with pears, but still interesting.

[tiplus]

Sounds interesting, do you guys have a blog at mashtime? What kind of hardware/software do you use for training? Tensorflow? on AWS or bare metal GPUs?

[iverjo]

We don't have a blog yet. We're using Azure for the hardware and mainly scikit-learn for the training (we train only on metadata at the moment). Will probably start using Tensorflow soon.

[doozler]

Would you say Tensorflow is a good way to get started with Machine learning?

[iverjo]

I'd say scikit-learn is a better way to get started with machine learning. Check this out, for example: https://www.youtube.com/watch?v=cKxRvEZd3Mw