Floyd - Heroku for deep learning

@ianmikutel There are loads of fantastic machine learning courses available for free. The first mention usually is the machine learning course by Andrew Ng on Coursera. Its highly recommended simply because Andrew is one of the pioneers of deep learning. be warned theres a lot of math inside, which makes sense because machine learning is 10% programming and 90% math. Udacity also has two incredible courses on machine and deep learning that i can highly recommend. another option is "machine learning a-z" on udemy (although id wait for another of their massive discount periods). closing up with my personal favorite course "practical deep learning for coders" by Jeremy Howard on YouTube. why is it my favorite? he gets practical very fast and yet still explains every mathematical detail. others may start with very dry theoretical bits. the course was also live recorded with actual students sitting in the room, who often ask just the right questions. however you should know a little about non-deep machine learning before taking that one. Id recommend starting with "Intro to Machine Learning" on Udacity and then continue with Jeremys course on YouTube. most importantly though: whatever you start with, stick with it. all of these are great. dont be stupid like me and lose time switching between courses to find your personal favorite.

@ianmikutel It's awesome that you're interested in learning! @gopietz That's a fantastic reply - thanks Pietz! Theory is obviously fundamental - and Pietz has mentioned some great resources. What works well, for me at least, is trying out some practical projects in parallel. Also helps keep me motivated. There are tons of open source repos on Github. Spin up a few iPython notebooks and play with code/tweak stuff and see how theory translates to results in practice. Here's a few Tensorflow iPython notebooks: https://github.com/floydhub/tens.... You can run these locally on your laptop. If you want to run them on Floyd, here's some instructions: http://docs.floydhub.com/guides/....

@taha_tweets Thanks! Definitely do want to lower the barrier to entry into deep learning.

@kleneway Thank you - appreciate the comment! We can't wait for you to try it too :)

@parkerwoodward *enabled by Floyd ™ would be awesome, haha :D

@brennenlb Thanks! Sorry about the wait. Lots more jobs than usual running right now and we're spinning up more machines to keep up with the traffic :)

@saip No Problem! Great Work!

@vishnugopal Thanks! We will be porting over a few popular DL algorithms and writing in depth guides over the next few days. Anything you'd like to see in particular?

@saip would love some demos of sentiment analysis, fraud detection & recommendation engines.

@vishnugopal Working on something for sentiment analysis! Will send out an update soon.

@prattarazzi Thanks! Glad you're finding it useful. We're working on some features the make the DL stuff easier/more productive too, so do keep an eye out :)