Everything you need to know about Machine Learning in 30 minutes or less
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Re: Everything you need to know about Machine Learning in 30 minutes or less
#2Hilary Mason has a longer introduction to machine learning video using web data, however, it isn't free.
Re: Everything you need to know about Machine Learning in 30 minutes or less
#3Hilary Mason has a longer introduction to machine learning video using web data, however, it isn't free. http://shop.oreilly.com/product/0636920017493.do
This looks really good. Thanks for the link
Re: Everything you need to know about Machine Learning in 30 minutes or less
#4Nice talk. The example of google translate is not a good one though. Say you translate from language A to language B with 99% accuracy, and vice versa, which would be pretty awesome, you'd still have a substantial quality decay after only a few back and forth translations (0.99^x where x is the number of translation steps).
Re: Everything you need to know about Machine Learning in 30 minutes or less
#5From the video, seems like this was a really tough crowd. Every other video I've seen with her speaking had people laughing and enjoying themselves.
Re: Everything you need to know about Machine Learning in 30 minutes or less
#6Nice talk. The example of google translate is not a good one though. Say you translate from language A to language B with 99% accuracy, and vice versa, which would be pretty awesome, you'd still have a substantial quality decay after only a few back and forth translations (0.99^x where x is the number of translation steps).
That's not a very realistic model of communication. If A communicates to B with 99% accuracy in the text, it's likely that B will 100% understand what's going. He will reply back to A with a 100% accurate message that's 99% accurate after translation, and so forth.
Re: Everything you need to know about Machine Learning in 30 minutes or less
#7If you already have a little exposure to machine learing, let me recomend an interesting review paper [1] on random forests: http://research.microsoft.com/pubs/155552/decisionForests_MS...
It isn't everything you need know in 30 minutes, but it's a concrete coverage of lots of topics in machine learning in under 150 pages. Here's why I'm recomending this paper:
* The algoritm is easy to understand.
* It can handle classification, regression, semi-supervised learning, manifold learning, and density estimation. The paper gives an introduction to each of these topics as well as a unified framework to implement each algorithm.
* It can handle categorical data and missing data [2]
* It gives as good results as other state of the art algorithms.
* The paper is well-written and easy to understand for someone without a deep background in machine learning.
[1] It's mostly a review paper. Using random forests for density estimation is new.
[2] This review paper doesn't cover categorical data or missing data.
Re: Everything you need to know about Machine Learning in 30 minutes or less
#8If you already have a little exposure to machine learing, let me recomend an interesting review paper [1] on random forests: http://research.microsoft.com/pubs/155552/decisionForests_MS... It isn't everything you need know in 30 minutes, but it's a concrete coverage of lots of topics in machine learning in under 150 pages. Here's why I'm recomending this paper: * The algoritm is easy to understand. * It can handle cl…
This is great! Thank you very much for sharing.
Re: Everything you need to know about Machine Learning in 30 minutes or less
#9Nice talk. The example of google translate is not a good one though. Say you translate from language A to language B with 99% accuracy, and vice versa, which would be pretty awesome, you'd still have a substantial quality decay after only a few back and forth translations (0.99^x where x is the number of translation steps).
That's not a very realistic model of communication. If A communicates to B with 99% accuracy in the text, it's likely that B will 100% understand what's going. He will reply back to A with a 100% accurate message that's 99% accurate after translation, and so forth.
I agree. But my impression was that she took the fact that google translate rapidly decays into gibberish as an indication that it's not doing a good enough job. I don't think you can argue that exactly because google translate does not have the interpretation capability.
Re: Everything you need to know about Machine Learning in 30 minutes or less
#10Earlier quoted context omitted.
That's not a very realistic model of communication. If A communicates to B with 99% accuracy in the text, it's likely that B will 100% understand what's going. He will reply back to A with a 100% accurate message that's 99% accurate after translation, and so forth.
I agree. But my impression was that she took the fact that google translate rapidly decays into gibberish as an indication that it's not doing a good enough job. I don't think you can argue that exactly because google translate does not have the interpretation capability.
Don't read too much into that example -- I chose it as a humorous metaphor, not a mathematical argument, and I messed up the delivery in the talk, anyway.
I'll refine the example for the next time!