Billing works through Stripe who accept debit cards as well. I’ll update the site to clarify.
@noskill 10 hours feels like enough time to try things out; the change helps keep Crestle sustainable long term. AWS doesn’t cover GPU instances under their free tier, so Crestle’s offer still works out to be better for users.
Oh, I see. It looks like Stripe does not support your particular card in India. Can you send me a DM with the type of card it is? I’ll get in touch with them to check.
Can you let me know if you will updating the github repo with the second course anytime soon? Also, the dogs-casts-redux dataset is in the /datasets folder as a zip file. Do we have to extract them to the user space to work on them or is it possible to extract them in the root directory and work (will reduce the usage space for user)?
I must say, this is one of the easiest workflows that I’ve experienced.
However, I cannot use it because the IO is a huge bottleneck (as it is with FloydHub; @sai, @narenst - you know this, I’m sure).
If you can somehow eliminate it, this has the potential to be the go to solution for cloud-based deep learning.
My experience, having started from nothing with fast.ai a few days ago, is that making everything work nicely on AWS took me about 10 hours, and even then I had poorly patched insecure systems. Making everything work up to the end of lesson 1 on crestle then took me about 20 minutes. including the compute time. Thank you very much, @anurag. I will persist with crestle for the next lessons.
Emrys: me too. From what I can tell, AWS no longer supports p2.xlarge, at least in my region. On to Crestle or TensorPort. I just hope the lesson instructions still work with these other resources.
Quick question, is it possible to get the connection information for the Jupyter notebook to allow other Jupyter clients to connect? I do a fair amount of work on an iPad while traveling and unfortunately the keyboard I have doesn’t an escape key! I’ve started using the Kernels app to connect to Jupyter to compensate for this and would love to be able to connect the two.
The URL you see when you open the notebook in a new tab is the actual Jupyter connection URL. Something like https://s.users.crestle.com/bgg3yzmo. The port is 443 since SSL is enabled. Try it out?