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Neural Networks Demystified

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Re: Neural Networks Demystified

#31

Post by albertzeyer »

pmalynin wrote: post #3
therobot24 wrote: post #2

no one can ever claim there that is a shortage of tutorials with regard to neural nets (and deep learning)

Tutorials - sure. Actual rigorous analysis - not at all.

What kind of analysis do you miss? There is a huge amount of research analysing all kind of aspects. See Schmidhubers overview paper oder Goodfellows Deep Learning book, or many other references to get an overview.

Of course, there are still many open questions. But I don't think that there is any aspect where there is no analysis available yet.

Re: Neural Networks Demystified

#32

Post by cJ0th »

V-2 wrote: post #28

At the risk of not sounding very clever, I have to admit it's way too fast for me

These (excellent) videos made me realize that picking up AI as a hobby (which I intended) would not be a good idea in my case. There are simply too many different domains of knowledge I would have to learn about to be able to finally do something slightly useful.

I neither have the time nor the brain to do this. Fascinating stuff, though.

Re: Neural Networks Demystified

#33

Post by colah3 »

JD557 wrote: post #23

In case the author of the videos is here, do you have plans to add some videos about Convolutional NNs and Recurrent NNs? I know a lot of developers like myself that know about traditional NNs, but are not familiar with those two.

Not the author, but I wrote an article introducing conv nets you might find helpful: http://colah.github.io/posts/2014-07-Conv-Nets-Modular/

I also have an article on RNNs, although it's focused on explaining a special version, called an LSTM: http://colah.github.io/posts/2015-08-Understanding-LSTMs/

If you have experience with functional programming, you might find this a nice way to think about Conv Nets/RNNs/etc: http://colah.github.io/posts/2015-09-NN-Types-FP/

Re: Neural Networks Demystified

#34

Post by V-2 »

cJ0th wrote: post #32
V-2 wrote: post #28

At the risk of not sounding very clever, I have to admit it's way too fast for me

These (excellent) videos made me realize that picking up AI as a hobby (which I intended) would not be a good idea in my case. There are simply too many different domains of knowledge I would have to learn about to be able to finally do something slightly useful. I neither have the time nor the brain to do this. Fascinating stuff, though.

My thoughts exactly. There's even too much of meta-knowledge here :) Without some solid background, it's not something you can casually pick up as a hobby. But yes, as a programmer (not dealing with anything AI-related - right now it's middle-of-the-road mobile apps) I am very impressed by what deep learning proves to be capable of

Re: Neural Networks Demystified

#35

Post by amelius »

rayalez wrote: post #13

Hey, everyone! I'm the founder of lumiverse.io, it's pretty incredible to see our website on the front page of HN! I want lumiverse to become an awesome community where people can discover and discuss great educational videos. We've launched only recently, the site is still in active development, I'm improving it every day. If you have any feedback - please let me know =) (Also feel free to contact me at raymestalez@…

Nice work!

It would be cool if there were pointers to recommended videos/courses from other organizations (Stanford, MIT, etcetera) for further learning.

PS: I would have wished my college classes had such relaxing background music :)

Re: Neural Networks Demystified

#36

Post by jordigh »

Why have neural networks become synonymous with backprop networks? Is it because those are the most successful? What happened to bidirectional associatve memory and Kohonen maps? Does anyone take the biological inspiration of neural networks seriously anymore?

Re: Neural Networks Demystified

#37

Post by limsup »

jordigh wrote: post #36

Why have neural networks become synonymous with backprop networks? Is it because those are the most successful? What happened to bidirectional associatve memory and Kohonen maps? Does anyone take the biological inspiration of neural networks seriously anymore?

people are mostly interested in what is successful and backprop/gradient descent (with certain specific architectures) is what has been dropping error rates on all sorts of tasks in recent years.

Re: Neural Networks Demystified

#40

Post by ldesegur »

pbz wrote: post #19
rayalez wrote: post #13

Hey, everyone! I'm the founder of lumiverse.io, it's pretty incredible to see our website on the front page of HN! I want lumiverse to become an awesome community where people can discover and discuss great educational videos. We've launched only recently, the site is still in active development, I'm improving it every day. If you have any feedback - please let me know =) (Also feel free to contact me at raymestalez@…

Feedback: 1) the videos go a tiny bit too fast in certain areas, but one can pause and rewind so that's not a problem 2) the background music is too loud/strong which makes it too distracting, I have to focus more than necessary on the spoken words; I'd cut the volume of the background music in half. Otherwise, pretty awesome videos :)

The music has to go. As a human, I can't focus with ambient noise. The rest is spot on. Keep up the great work.
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