Everything you need to know about Machine Learning in 30 minutes or less

http://www.hilarymason.com/presentations-2/devs-love-bacon-everything-you-need-to-know-about-machine-learning-in-30-minutes-or-less/?utm_source=twitterfeed&utm_medium=twitter

by gmodena • 14 years ago

204 15 14 years ago

hilarymason.com

kqr2• 14 years ago

Hilary Mason has a longer introduction to machine learning video using web data, however, it isn't free.

http://shop.oreilly.com/product/0636920017493.do

ramblerman• 14 years ago

This looks really good. Thanks for the link

marcelsalathe2• 14 years ago

Nice 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).

vecter• 14 years ago

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.

marcelsalathe2• 14 years ago

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.

ninjin• 14 years ago

Not that I am doing Machine Translation (MT), but saying accuracy is a bit vague. The whole notion of what is lost in a translation using MT is to the best of my knowledge not fully captured with any well-established measure.

Fair warning, I haven't had time to have a look at the video (short break at work). I'll do it once I get home.

jtagen• 14 years ago

From 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.

monk_the_dog• 14 years ago

If 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.

five_star• 14 years ago

This is great! Thank you very much for sharing.

droz• 14 years ago

http://lasa.epfl.ch/teaching/lectures/ML_Phd/Notes/ML_Lectur...

Is another great resource that introduces many ML topics from the ground up.

geoffw8• 14 years ago

Gutted. I was there on the Friday, but not the Saturday (which is when the exciting stuff was). The BrewDog talk was best!

taliesinb• 14 years ago

For more advanced audiences, here's a great resource I discovered recently: http://videolectures.net/mlss09uk_cambridge/ -- 60 hours of lectures from the giants of machine learning delivered at a summer school held at Cambridge in 2009.

Everything you need to know about Machine Learning in 30 minutes or less

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