[mza]

GM for AI at AWS here: actually - we like TensorFlow quite a bit, too.

We provide a machine image with TF, MXNet and others pre-installed, along with Keras, CPU and NVIDIA divers, and other libraries for deep learning. We just added Ubuntu support too:

https://aws.amazon.com/blogs/ai/the-aws-deep-learning-ami-no...

[boulos]

Sorry if that wasn't clear from my opening (both providers offer the DIY option, and are happy to support every ML framework). I think for folks looking to have a hosted TF service though, we wouldn't expect that (sadly) from AWS, particularly after the MXnet announcement:

http://www.allthingsdistributed.com/2016/11/mxnet-default-fr...

but to each his own!

[pilooch]

https://aws.amazon.com/marketplace/search/results?searchTerm... Some more AMIs for deep learning.

[MrQuincle]

The challenge is always to get a lot of training data.

Are there (artificial) datasets that can be used that showcase particular fit for deep learning?

I think there is way to little research in building artificial datasets (using domain knowledge of course).

It might even be possible to run these generative models and have this type of data very soon.

[boulos]

ImageNet, GoogleNet, etc. are all image datasets for precisely this purpose. There's also the recently announced YouTube dataset and Kaggle challenge [1] and Google Research's datasets [2].

I agree though, the kind of artificial / play-against-yourself datasets that the folks at DeepMind created for say Alpha Go are an entirely different beast.

[1] https://cloud.google.com/blog/big-data/2017/02/google-cloud-...

[2] https://research.google.com/research-outreach.html#/research...