11–20 of 32 posts
This book is everything I've ever wanted in a programming text. I'm sorry that I don't have much of anything substantial to say except praise, but seriously, thank you for writing this.
Does anyone have any examples of areas where neural networks beat out statistical based methods, other than maybe image recognition? I can't even think of another major area where they dominate. - Search engines use algorithms, not neural nets. - The most popular algorithm on Kaggle (data analysis competitions) is random forests - Google's self-driving car uses statistical-based methods I can't imagine commercial air…
Does anyone have any examples of areas where neural networks beat out statistical based methods, other than maybe image recognition? I can't even think of another major area where they dominate. - Search engines use algorithms, not neural nets. - The most popular algorithm on Kaggle (data analysis competitions) is random forests - Google's self-driving car uses statistical-based methods I can't imagine commercial air…
Search engines could use neural networks (and possibly have better search results), but the research was just done a few years ago (ie 3-4 years ago) and search engines are much older than that.
As for the commercial aircraft point: I'm trying to find the youtube video I've seen before about this. The video is of a plane simulation where the plane has lost control of both of the wing flaps (or both of some other important steering element) and a person was unable to stabilize the plane but a neural network could. This doesn't mean a neural network should be used for autopilot all the time, but they can be useful for certain situations.
Edit: found the video, https://www.youtube.com/watch?v=aObBHXsc_iw&t=3m50s
Does anyone have any examples of areas where neural networks beat out statistical based methods, other than maybe image recognition? I can't even think of another major area where they dominate. - Search engines use algorithms, not neural nets. - The most popular algorithm on Kaggle (data analysis competitions) is random forests - Google's self-driving car uses statistical-based methods I can't imagine commercial air…
the system is fed with the actual transcript for some videos so it can learn with time and minimize error.
the overall system is incredibly useful as you can search the video stream of a TV channel for a specific keyword.
I have also used self organizing maps before for creating a recommendation engine.
I think it works a better than typical recommendation engines because you can feed the network features based on multiple criterias (in addition to taxonomies, you can also feed user geographic location, and click patterns etc ..)
Does anyone have any examples of areas where neural networks beat out statistical based methods, other than maybe image recognition? I can't even think of another major area where they dominate. - Search engines use algorithms, not neural nets. - The most popular algorithm on Kaggle (data analysis competitions) is random forests - Google's self-driving car uses statistical-based methods I can't imagine commercial air…
Definitely image recognition: http://www.cs.toronto.edu/~hinton/absps/imagenet.pdf
Speech recognition: http://www.cs.toronto.edu/~hinton/absps/RNN13.pdf
Natural language processing: http://www.socher.org/index.php/DeepLearningTutorial/DeepLea..., http://aclweb.org/anthology/N/N13/N13-1090.pdf
If you're into kaggle competitions: http://blog.kaggle.com/2012/11/01/deep-learning-how-i-did-it...
I don't think there are going to be any further major advances in eg SVMs or random forests (famous last words maybe...) Neural nets, on the other hand, are just scratching the surface of what's possible. So right now they are state of the art in some historically very difficult areas. But these are early days still.
Does anyone have any examples of areas where neural networks beat out statistical based methods, other than maybe image recognition? I can't even think of another major area where they dominate. - Search engines use algorithms, not neural nets. - The most popular algorithm on Kaggle (data analysis competitions) is random forests - Google's self-driving car uses statistical-based methods I can't imagine commercial air…
Glad you asked... Definitely image recognition: http://www.cs.toronto.edu/~hinton/absps/imagenet.pdf Speech recognition: http://www.cs.toronto.edu/~hinton/absps/RNN13.pdf Natural language processing: http://www.socher.org/index.php/DeepLearningTutorial/DeepLea... , http://aclweb.org/anthology/N/N13/N13-1090.pdf If you're into kaggle competitions: http://blog.kaggle.com/2012/11/01/deep-learning-how-i-did-it... I don't…
As to the GP: Geoff Hinton (probably the most well-known neural networks researcher) said in his Coursera course that neural networks thrive at problems with a lot of structure that could be encoded, while simpler models like SVMs or Gaussian processes might be better for problems without as much deep structure to discover.
Also, a lot of the current research with neural networks involves using neural networks to learn better representations of data. These cleaner representations of data (which can be thought about as a sort of semantic PCA) often make classification far easier, which explains the great results. Learning representations also makes transfer learning (transferring knowledge from one domain to another) much easier/more possible.
An awesome book; I've now started reading from the beginning of the book :) One thing I've noticed though, is that img 10 of chapter 1 is missing. http://natureofcode.com/book/chapter-1-vectors/imgs/chapter0...
I think that's so amazingly awesome, that it can evolve as a living document in this way.
Here is a test with a model of a robotic arm: https://assemblino.com/show/public20123372.html
Does anyone have any examples of areas where neural networks beat out statistical based methods, other than maybe image recognition? I can't even think of another major area where they dominate. - Search engines use algorithms, not neural nets. - The most popular algorithm on Kaggle (data analysis competitions) is random forests - Google's self-driving car uses statistical-based methods I can't imagine commercial air…
http://www.fico.com/en/Products/DMApps/Pages/FICO-Falcon-Fra...