Machine Learning Fairy Dust
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Machine Learning Fairy Dust
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Re: Machine Learning Fairy Dust
#2I was nodding my head u til I got to the end - it seems like the google prediction API _is_ the magic fairy dust we've been waiting for?
Re: Machine Learning Fairy Dust
#3I think 'machine learning' is so complex that people just don't feel like trying to explain it. That, or their business secrets are tied up in it, and they don't want to give away the golden goose.
Re: Machine Learning Fairy Dust
#4I was nodding my head u til I got to the end - it seems like the google prediction API _is_ the magic fairy dust we've been waiting for?
I think his point is that it's just a tool that makes it a little easier for startups to incorporate machine learning into their products - like he said, it may be appropriate for some types of problems, but not all. But I'm sure we'll start to see more tools like that become more widely used.
When AJAX first came out, not everyone knew how to do it - but now, everyone can drop in jQuery and do all sorts of complex things relatively easily.
Re: Machine Learning Fairy Dust
#5I was nodding my head u til I got to the end - it seems like the google prediction API _is_ the magic fairy dust we've been waiting for?
I think his point is that it's just a tool that makes it a little easier for startups to incorporate machine learning into their products - like he said, it may be appropriate for some types of problems, but not all. But I'm sure we'll start to see more tools like that become more widely used. When AJAX first came out, not everyone knew how to do it - but now, everyone can drop in jQuery and do all sorts of complex t…
I guess that a good point. I wonder what kinds of bad implementations of the api we'll see. What a great revenue stream for google - what startup won't use the api in some way? I know i'm setting it up tonight and using it on at least one project.
Re: Machine Learning Fairy Dust
#6I think 'machine learning' is so complex that people just don't feel like trying to explain it. That, or their business secrets are tied up in it, and they don't want to give away the golden goose.
That's an explanation for some of the examples, but I think a lot of the times it's actually really simple, along the lines of, "we sift through some data and correlate it". The odd thing is, that often works, especially for user-facing perceptual stuff where there's a strong placebo effect, even more especially if you salt liberally with some hand-tuned biasing. Sort of how The Sims is able to use some super-simple algorithms to give the impression of interesting characters.
However, if you do need some real magic to be done, and your product really won't work without it, then things get trickier; bad statistics, or at least statistics not really used correctly, is really common in the innards of these kinds of products.
Re: Machine Learning Fairy Dust
#7Its fine if people want to say that ML will take care of the "details" ...let them try to use ML right and they will see you need to spend a long time understanding how to do things right. Most of the time, you can't use linear regressions right out of the box, let alone SVM's.
Re: Machine Learning Fairy Dust
#8Its fine if people want to say that ML will take care of the "details" ...let them try to use ML right and they will see you need to spend a long time understanding how to do things right. Most of the time, you can't use linear regressions right out of the box, let alone SVM's.
Agreed. The use of ML is highly dependent on the data. Having a something like the Prediction api is fine, but seems like the use-cases would be rigid.
Re: Machine Learning Fairy Dust
#9I was nodding my head u til I got to the end - it seems like the google prediction API _is_ the magic fairy dust we've been waiting for?
I think your comment is an example of the point of view that the author was talking about. The Google Prediction API won't automate the process of grouping comments or stories by content. Someone has to do the work of collecting the data and preparing the corpus, determining the best way to analyze it and prepping the inputs and outputs. There are levels of understanding and effort between having an idea involving machine learning and getting accurate predictions.
The google prediction api takes care of the code for algorithmic computation. While that's handy, it's only one step of a much larger process. The scale of that process is something that many people don't fully understanding about machine learning (yet).
Re: Machine Learning Fairy Dust
#10The cloud will solve it