[altonzheng]

Any idea on how this compares to the deep learning course here: http://course.fast.ai/?

Very interested in taking a course, but there are so many offerings available. I have high level ML understanding from classes I took in college, but wanted to dive deeper into it.

[laurentmih]

The fast.ai course does what it says on the tin: it's a practical approach to deep learning. I know I'm being lame by copying their tagline, but it really does just that: it has a no-frills approach to _applying_ deep learning. What you'll see:

* How to build and train a convnet

* What transfer learning entails

* How to build and train an LSTM

* How to build and train a 'vanilla' neural net

What you won't be covering:

* The difference between ADAM and EVE optimizers

* The mathematics behind backpropagation

* The mathematical 'theory' behind 'exploding gradients'

In brief: fast.ai is all about having coders get started with deep learning ASAP. If you have theoretical questions, the answer will usually be a one-liner, along with "but that's out of scope for this class".

I loved it to pieces, I think it's fantastic and a must-do if you've got any Python affinity. You would not believe what you, a run-off-the-mill programmer, have as a power when it comes to getting ConvNets/Nnets/LSTMs do. You can really build powerful, (almost) Google service level stuff.

But it's not very detailed on theory.

[plusepsilon]

Ya it seems like just another deep learning course.

I can vouch for fast.ai though. They're the best if you're just starting.

[mino]

+1

fast.ai is probably the best MOOC I've ever followed. As its name says, it is "for coders" and 100% applied. It is perfect for getting started, quickly.

Please read this blog post, in particular regarding the comment on "Hacker News contributors regularly give such awful advice on machine learning".

http://www.fast.ai/2017/03/17/not-commoditized-no-phd/

and:

http://www.fast.ai/2017/03/23/focus-on-coding/