> Neural Networks are gradually taking over from simpler Machine Learning methods And haven't SVMs and such gradually taken over from Neural Networks?
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Neural Networks for Machine Learning
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Re: Neural Networks for Machine Learning
#32> Neural Networks are gradually taking over from simpler Machine Learning methods And haven't SVMs and such gradually taken over from Neural Networks?
The way it's worded is not 100% clear. Hinton, who is an excellent lecturer and explainer, is talking about neural nets trained with "deep learning" techniques (not vanilla single-hidden-layer nets), which have had striking success at hard vision problems that have been difficult to solve top-to-bottom with SVMs (e.g., you could get good performance from an SVM, but you'd have to go on a hunt for good low-level features first).
That said, there is a rather unhelpful herd mentality in the field, with people moving from one Next Big Thing to another, disparaging the previous Big Thing along the way.
Re: Neural Networks for Machine Learning
#33I tried to do a couple coursera courses and found the video lectures highly inefficient; very needlessly time consuming, even watching them sped up. All I really want is a glorified text book with quiz grading and a final.
It depends on how much you value your time. Lectures usually are shorter than 2 hours per week. (There are some that have longer videos, but I think more than 2 hours is suboptimal.) I know that before courses I was wasting this time on hacker news or reddit, so I don't value my time that much. On the other hand I do now, and that's because I need to watch the lectures and do the home work. And really these lectures perform the same role in the learning process as the real lectures. You could graduate from university only with text books, but you might not get some insight that lecturers have.
My 0.02 chf.
Re: Neural Networks for Machine Learning
#34Just browsing through the Coursera Computer Science listings, it looks like they are rapidly approaching the point where you could put together a CS curriculum superior to what you could get at any single school. The people they have teaching a lot of these topics are some of the best in the world in their field. The Micahel Collins NLP course looks really thorough and up to date, for example I took a similar course…
An attempt to design a reasonable computer science curriculum using just Coursera courses, where “reasonable” is a curriculum that roughly mirrors the coursework required for a four-year university computer science degree:
http://www.thesimplelogic.com/2012/09/24/you-say-you-want-an...
Re: Neural Networks for Machine Learning
#35> Neural Networks are gradually taking over from simpler Machine Learning methods And haven't SVMs and such gradually taken over from Neural Networks?
And RandomForests taken over from SVMs ;)
In seriousness when you look around at what's happening both in practice and in academia I would say RandomForests/SVM/Neural Networks all stand pretty equally and have different strengths. If you've just got rows and rows of data with numeric, categorical and missing values it's hard to beat the speed and quality of shoving it in a RandomForest. However to my knowledge SVMs are still better at solving NLP categorization tasks and handling sparse, high dimensional data. And Neural Networks always seem to be popping up solving very weird and/or hard problems.
Re: Neural Networks for Machine Learning
#36> Neural Networks are gradually taking over from simpler Machine Learning methods And haven't SVMs and such gradually taken over from Neural Networks?
Well not quite. While SVMs gained a lot of popularity for having nice properties e.g. 1) a convex problem which means a unique solution and a lot of already existing technology can be used 2) the "kernel trick" which enables us to learn in complicated spaces without computing the transformations 3) can be trained online, which makes them great for huge datasets (here the point 2) might not apply - but there exist way…
Enlightening response, could you please post links to papers that explain online training of SVM?
Also, I found this paper [1] on unsupervised feature detection, if you have some additional material, I'll really appreciate if you could post it!
[1] http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.44....
Re: Neural Networks for Machine Learning
#37people are already complaining that you can only take the quizes once ... he had to send out an email today to everyone saying: "Many of you are unhappy with only being allowed to attempt a quiz once. Starting in week two, we have therefore decided to make up twice as many questions and to allow you to do each quiz twice if you want to. The second time you try it the questions will all be different. Your score will b…
Yeap we got spoiled with earlier classes: Algorithms by Tim Roughgarden, Machine Learning by Andrew Ng, and many more. We probably need to follow a class on gratitude.
Oh well, to be fair I would donate quite a lot for each course that I enjoyed.
Re: Neural Networks for Machine Learning
#38The only course that is not significantly diluted is Koller's PGM. All others have been dumbed down to a degree where they provide no challenge to the courseree at all.
It is not such a huge problem when you take several courses at once. Sadly they run them only twice a year, each time I try to follow as many as possible. I cannot follow PGM because it requires too much of my time, I'd have to abandon 2 or 3 other courses. YMMV.
Re: Neural Networks for Machine Learning
#39I'm in the middle of the machine learning coursera course, and registered for this one as well due to interest in the material. My one complaint is that the programming assignments weren't interesting at all. The results were interesting, but the setups were mostly given to us, and we just had to code an algorithm that was in our notes. For someone who understands the basics of linear algebra and programming, it was…
I've taken both, and the code is in fact not that much simpler than it was in the original class. There are, however, two huge differences: the algorithm is spoon-fed to you, and there is no math. Firstly, think about how much more difficult the assignments would be if, for example, the steps weren't broken out and we didn't get any advice on how to vectorize. Of course, it would still be short work for anyone who (a…
(slightly old) lecture videos for CS 229: http://www.youtube.com/course?list=ECA89DCFA6ADACE599
Re: Neural Networks for Machine Learning
#40I tried to do a couple coursera courses and found the video lectures highly inefficient; very needlessly time consuming, even watching them sped up. All I really want is a glorified text book with quiz grading and a final.
It sounds terribly privileged to say so, but I'm afraid I have to agree. Also, quite often the quizzes are directly based on the videos ("What did line A represent in ~ graph?"), while I find I self learn better through reading.