
Learning From Data - Online Course - LiveTheDream
http://work.caltech.edu/telecourse.html
======
andymatuschak
Yaser Abu-Mostafa was (by enormous margin) the most effective professor I had
at Caltech. Despite being such an expert in the field, he understands clearly
when a concept is particularly challenging--and what about it makes it so.
This class (the official equivalent) was one of my absolute favorites.
Definitely worth a look!

~~~
evan-arm
What Andy says is absolutely true. This machine learning class was easily the
best class I took at Caltech. Prof. Abu-Mostafa got a standing ovation at the
end of the course the term I took it. I wish I could have taken more of his
classes.

It was also fairly difficult -- the assignments were hard, but at every step,
you could look at what you'd done and say "I know why I'm doing this, and I
can see how this works."

I remember at the end of the term he took several students' notes and made
copies of them, so that he could compare the students' notes with what he was
trying to convey, and could know if he wasn't teaching certain parts of the
class well enough.

It's a shame that not all professors are as dedicated and responsive to their
teaching obligations as Prof. Abu-Mostafa.

Oh, also, "introductory" in this context is meant to differentiate it from
"graduate level". Every student (mostly juniors and seniors) in this class
will have had several terms of math, theoretical CS, and practical programming
classes.

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tel
This looks like the kind of class more people need to see. It's less "how to
implement" things and more why things do or don't work.

I find this dreadfully important because when you study this math you realize
that more often than anyone expects, standard ML is extraordinarily fragile,
but also has some powerful justification. For instance, this[1] made me laugh
with joy.

[1] <http://work.caltech.edu/images1/canvas.png>

~~~
scoot
> this[1] made me laugh with joy.

Whereas it went completely over my head...

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Stratego
Online teaching is not so much about watering down than understand that your
audience will not usually and probably cannot have the same level of focus
that your on-campus students will have. It's not a judgement of skills, but a
simple observation of psychological incentives.

Online is a great place to learn, but it's absolutely the wrong place to learn
the exact same curriculum as offline.

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codenerdz
These seem to be LIVE videos of the lectures broadcast during the workday in
US. Their previously recorded page states that they will only provide videos
of the first week. Not really doable by anyone in US timezone with a job.

~~~
caycep
i sent an email to clarify - i think they will have them available for
download on the site after the live lectures.

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heifetz
the best aspect of the andrew ng course was the homeworks using octave. Yes,
it's watered down and not as mathematically rigorous as the real course, but
you learn a lot of the essentials from the experience of coding machine
learning algorithms, that I can't imagine learning as easily from doing non-
programming homework.

~~~
aseembehl
Prof. Ng's class wasn't watered down. CS229A(<http://cs229a.stanford.edu/>) is
the Stanford equivalent of the online ml-class. Ng also teaches another
machine learning course at stanford(CS229) which focuses on the theoretical
underpinnings of ML.

~~~
ojbyrne
Having taken the online course, I'm not sure I understand you - the
programming assignments in some cases required 1 line of code be written (in
the middle of a more complex program). I find it really hard to believe that
students who pay tuition would be given the same assignments.

~~~
aseembehl
CS229A is a course taken by people from different backgrounds not just CS. It
basically deals with the practical aspects of machine learning, implementation
issues etc. In addition to the lectures and the assignments, stanford students
also had an additional course project.

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mrleinad
Anyone knows if a video for each class will be available after live streaming?

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lightcatcher
As an undergrad at Caltech who will be taking this course next term, I find
this intriguing. I'm wondering if this course will be as popular as the
Stanford courses (looks like a lot less effort is being put into organization,
design, etc) and how the difficulty of this will compare to the Stanford
courses and an average Caltech course.

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sev
Homeworks? Lack of a sign-up link? Interesting that they have grammatical
errors on this page considering their goal here (to compete with other top
universities doing the same thing)

~~~
kliao
who says they are trying to compete with other universities? the goal here is
to provide quality education accessible to everyone. it also looks like the
webpage was created by the professor himself (<http://work.caltech.edu/> is
his personal page) and may not be completely ready yet.

~~~
sev
So, they have no interest in being the best at what they do? I would hope not.
And yes, details make a difference.

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cop359
The course seems all over the place. You learn very little about a lot of
things... The topics don't really seem to build on each other. I'm not sure
that's a good thing.

~~~
CurtHagenlocher
If this is anything like the classes I took as a Caltech undergrad, you will
not learn "very little". Or if you do, you won't pass the class.

~~~
cop359
In total it might be a lot, but it can't be indepth. for example "Error and
Noise" is something you can spend a whole year studying. What are you really
going to cover in one lecture? You'll just touch on a few things that might be
useful at some point, but you're not building a larger encompassing
understanding of "Error and Noise".

I've taking classes like this. You learn a few useful tricks, but when shit
hits the fan in the real world and your tools are not enough you're left
floundering. You can't prove things, you can't develop your own methods
because you don't understand the principles they're based on.

This would probably be a cool class to take freshman year so that you can
figure out for yourself what you'd like to study.

~~~
snikolov
This is clearly an introduction. You're not going to spend a semester talking
about "Error and Noise" in a class like this. I had the opposite impression
--- that it covers a relatively small number of topics that are very highly
related.

Now, will you come out of this class knowing how to do practical machine
learning? Probably not. But these are fundamental concepts that you must know.
When your tools are not enough in the real world, you can appeal to these
concepts to understand why.

------
jongraehl
Andrew Ng's course[1] covers the same ground and was excellent.

[1] <http://www.ml-class.org/course/auth/welcome>

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psychotik
Is there any reason to watch this live, instead of catching it on iTunes U or
downloading older videos for later viewing? Just curious if there's something
I'm missing something that adds value one way or another.

~~~
benohear
As I understand it, it's not only about watching the lectures but actually
taking the course (with assignments and all). For that to work, it makes sense
to be on the same schedule as the "real" students.

That said, I'd quite like to just watch the vids sometime later. Anyone know
if / where they will be available?

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plessthanpt05
Cool that so many things like this are popping up lately: Tom Mitchell at CMU
putting up all of his lectures/material, the Stanford/coursera ML course, now
this CalTech course... are there others?

~~~
benohear
MIT: <http://ocw.mit.edu/index.htm>

~~~
plessthanpt05
was mostly thinking of courses that had lectures/vids up, but that also
reminds me of this berkeley course i came across on HN a couple of weeks ago:
<http://alex.smola.org/teaching/berkeley2012/>

~~~
benohear
But they do. For example:

[http://ocw.mit.edu/courses/electrical-engineering-and-
comput...](http://ocw.mit.edu/courses/electrical-engineering-and-computer-
science/6-00-introduction-to-computer-science-and-programming-fall-2008/video-
lectures/)

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zeratul
The course teacher's book costs $828 + $4 shipping:

<http://www.amazon.com/gp/offer-listing/1600490069/>

Is this an error?

~~~
charliel
From <http://amlbook.com>, which is hidden within the page
<http://www.amazon.com/gp/product/1600490069>, the book will become available
on Mar26 on amazon for $28, not $828.

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rdssassin
hmm the commitment of watching the lectures live at a certain time is a bit of
a negative for me

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ndefinite
Did anyone see a sign up link?

~~~
vilya
No, but it does say "registration will be open next week" in big letters...

~~~
ndefinite
Ah, I completely missed that

