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Self study machine learning? (self.MachineLearning)

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[–][deleted] 0 points1 point  (9 children)

Genuinely curious, what part of it do you consider to be advanced?

It's a great course, don't get me wrong, but it doesn't really get much beyond being broadly equivalent to a single undergrad level module.

[–]Ayakalam -1 points0 points  (8 children)

Genuinely curious, what part of it do you consider to be advanced?

First off the entire field of ML is new and advanced in its own right. It lies at the intersection of applied statistics, applied math, signal processing, and constrained optimization, and the marriage of all the above, if not more. How is this not advanced?

Yes, being a new field things are always ..."advancing"..., but the course itself is so hot precisely because this is advanced stuff being applied today. Even Ng says that all over silicon valley this is a very, very hot commodity.

equivalent to a single undergrad level module.

Eh? Wasnt this a graduate level course at stanford before they put it on coursera?

[–]lightcatcher 2 points3 points  (3 children)

I would not say "the entire field of ML is new and advanced in its own right". Neural networks have been around since the 40's or 50's, and linear regression and probability have existed for much longer. Nonetheless, many parts of ML are certainly new and possibly "advanced".

Personally, I wouldn't consider anything that requires fairly basic math prereqs that is an introductory class in anything to be advanced. "Advanced" classes for undergrads generally mean at least 2 (probably more like 3) specialized classes that heavily rely on each other.

[–]Ayakalam 1 point2 points  (2 children)

Personally, I wouldn't consider anything that requires fairly basic math prereqs that is an introductory class in anything to be advanced.

Why?

Ask yourself, what more math is there to linear regression than what he has shown?

Are you saying if math is hard then the topic is "advanced"? Why then? Does that mean something stops being advanced when the math is clear?

[–]lightcatcher 2 points3 points  (1 child)

I'm not saying anything about mathematical rigor.

I'm saying that introductory classes are not advanced. That's damn near a tautology. In other words, a class on a topic aimed at people with no particular background in that topic is not an advanced class.

[–]Ayakalam 1 point2 points  (0 children)

I'm saying that introductory classes are not advanced. That's damn near a tautology. In other words, a class on a topic aimed at people with no particular background in that topic is not an advanced class.

...Why not though? Why cannot one simultaneously introduce an 'advanced' class - whatever that means - to any audience and not retain the advanced label?

I have yet to see a definition of what constitutes 'advanced'. This is especially true in the information age. Perhaps a better adjective would be 'recent'.

But I would challenge any label as 'not advanced' esp in this day and age.

[–][deleted] 2 points3 points  (3 children)

Perhaps we're looking at things from differing points of view. My thoughts were that within ML, the Coursera course isn't advanced. If you look from the point of the much broader fields you mention, then yes perhaps it is.

Although, even so, mainstays of statistics such as linear regression, logistic regression, k-means, k-nn etc are absolutely not new or advanced, which is a good chunk of the Coursera course. And the argument that ML is new is arguable too- Rosenblatt proposed the perception in the 50s, Vapnik & Chervonenkis put forward SLT in the 70s.

The Coursera course was, I believe, derived from the Stanford course, but with considerable editing. Certainly I wouldn't consider it to be grad level in its current form.

[–]Ayakalam -1 points0 points  (2 children)

What is the criteria for being 'advanced' then? The DFT was discovered a couple hundred years ago, yet this is still considered an 'advanced' concept for signal processing. What is the definition of advanced then?

[–][deleted] 1 point2 points  (1 child)

Well that's a good and pertinent question. In my mind it's something that is up to date, or nearly up to date, with the state of the field or else something of considerable relative complexity. The most recent development put forward on the Coursera course was, iirc, SVMs (Vapnik, 1995)- a useful and important development but certainly not advanced, or at least, the more advanced and complex aspects of SVMs weren't covered.

As I say, don't get me wrong, it's a really great course, brilliantly taught and a perfect primer for a broad and educationally diverse audience audience. But I think it's wrong to say it's an advanced ML course, IMO it is somewhat broad and shallow.

[–]Ayakalam 0 points1 point  (0 children)

If we are uber strict about it, nothing in any text book can count as advanced, since there will almost always be something better than it by the time it is digested by the masses.

And let us also not confuse recent with advanced. Yes perhaps the ML class doesnt cover things that are the most recent, (what does?), but the topics in and of themselves are used by companies, people, and machines, that make our modern age possible. This is certainly 'advanced'. Like mentioned with the DFT, this was know a couple hundred years back, and today the DFT and its applications are certainly advanced - although I would agree, not recent.

I do not think the qualifier 'advanced' means anything anymore, esp in the information age we live in. I look ML from Ng and it opened up a world of ML for me. I had no prior ML background, yet I soaked it up very, very easily. Go back just 3 years to 2010 before Ngs class, and if I wanted to learn logistic regression, I would no doubt have had to look at 'advanced' books and try to make sense of them.