

Stanford's online Machine Learning class now open for enrollment - roger_lee
http://www.ml-class.org/course/auth/welcome

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amirmc
Just as a reminder for folks, there's a spreadsheet of HN readers who are
taking part in the classes at <http://bit.ly/pLCRzg>

There are 120+ HNers on there so you might find folks nearby you'd like to get
in touch with.

Edit: Obviously, if you're doing any of the courses feel free to add your
details too

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vl
I wonder if taking both ai-class.org and ml-class.org is going to be too much
load for a person who is working full-time and if they are going to cover a
lot of the same topics or not? Does anyone have an insight?

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jzawodn
I wonder the same and am having a tough time deciding which to take (or both).

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webspiderus
for what it's worth, if you take the ML class, you will learn most of the
things you would learn in the AI class and more - although it does get a bit
rigorous, and will take more time than the AI class would. from personal
experience, I feel like Ng's class gave me a more thorough foundation in the
math behind the concepts, and was more challenging to boot - so I'd recommend
it if you're feeling up for it.

~~~
plinkplonk
I was just informed that Stanford's online ML course is based on CS229A rather
than CS 229.

From the CS229A home page

"This class' emphasis is on Applied Machine Learning. Concretely, we want to
give you the practical skills needed to get learning algorithms to work.
Compared to CS229 (Machine Learning), _we cover fewer learning algorithms, and
also spend less time on the math and theory of machine learning_ , but spend
much more time on the pratical, hands-on skills (and "dirty tricks") for
getting this stuff to work well on an application. More of the homeworks will
also focus on giving you practice implementing, modifying and debugging
learning algorithms, and less on the mathematical underpinnings of machine
learning"

the core idea seems to be that this is a simplified and less rigorous version
of CS 229. I am not sure of the tradeoffs between acquiring the "dirty tricks"
vs getting a solid grasp of the underlying math (which would presumably result
from taking CS229)

Can anyone at Stanford tell me about how much difference is there in the
perceived relative toughness of CS229 vs CS 229A? Do CS students take 229A or
is it more people from the industry and other (non CS/Math) branches?

Any opinions greatly appreciated.

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webspiderus
I can relay some of the things Prof. Ng said in the first meeting of the
CS229A class:

229A is definitely meant to be much less mathematically rigorous - he said
that he expects some people who don't feel like they're necessarily up to 229
to take 229A first to gain more familiarity with the material. From the people
that actually showed up to the lecture, it was mostly CS people - although
it's hard to say what the online enrollment is like. It is definitely meant to
be useful to anyone who wants to be able to get machine learning algorithms to
work, not necessarily understand their finer points.

~~~
plinkplonk
Thanks a _lot_. I am fluent in the pre req math and proving theorems and build
ML based real world systems for a living. I just wanted to take a classic
class and see what it felt like. I think I'll wait for the online version of
229 then (if there is one in the future).

Thanks again. You saved me a lot of time. Much obliged. HN rocks.

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HSO
Perhaps this is the place and occasion to ask this question:

What's the advantage of taking this class over reading a good (text)book incl.
exercises contained therein?

I realize people have different learning styles and I'm just not the type who
learns well from listening. Still, even though I hated going to classes in
school and university, I'm tempted by these offerings (AI, ML, DB). Perhaps
I'm just looking for an excuse.

So, anyone here who can give some good reasons for why taking this course is
better than (or adds to) a "mere" book?

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pakitan
I, too, am of the the type that learns better by reading, rather than
listening but this format provides some additional "incentives" for the
hardcore procrastinator who plans to read that AI textbook "later". Most
important of all, if you want to complete the course, you're forced to follow
a schedule and there are no excuses. Then there is the "reward" factor -
you'll be getting a certificate and also all students are ranked based on
their exam scores = you'll be motivated to work harder. Last but not least,
the instructors will answer student questions about the course material.
That's not something you can get from a book.

These are the reasons why I signed up.

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Tycho
Am I likely to learn anything of immediate practical benefit on this course?
I'm not a computer scientist, just someone who writes lots of scripts to work
with Unix/Excel/RDBMS/XML for a finance company.

(not that this would discourage me from taking the course, I'm just curious
whether it will give me some new tools on my swiss-army-knife of programming
knowledge, for my day job)

~~~
silentbicycle
For a quick overview of some machine learning fundamentals, you could check
out Hilary Mason's "An Introduction to Machine Learning with Web Data"
(<http://shop.oreilly.com/product/0636920017493.do>) videos. They cover
classification & clustering, with theory and a quick intro to some relevant
Python libraries.

For your purposes, one potential use could be combing through lots of
financial data for transactions that look unusual. (Another very common use
for classification is spam filtering.)

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seancron
I'd also recommend Programming Collective Intelligence
(<http://shop.oreilly.com/product/9780596529321.do>) which is filled with lots
of python code showing how different algorithms and techniques can be used.

~~~
silentbicycle
I thought about suggesting that, but when I started working through it, I kept
running into errors in the code and formulas. He explains the concepts well,
though.

_Artificial Intelligence: A Modern Approach_ by Russell & Norvig ("AIMA") is
also quite good, though a bit more demanding of the reader.

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Sargis
How difficult would this be for someone with minimal linear algebra knowledge?

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dpeck
From the course page:

No particular math background is assumed, and we will go over the math
concepts you need in the first couple of weeks.

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Homunculiheaded
However pretty early in the lectures they jump right into taking partial
derivatives of matrices for calculating gradient descent. I think by 'no
particular math background' they mean 'assuming nothing more than single and
basic multivariable calculus plus linear algebra'. If your linear algebra
and/or multi-variable calculus are weak/fuzzy (as they are for me) I think
those sections will take quite a while to really understand.

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rcavezza
I have a business background and I taught myself to code after getting
involved in startups. I'm in the middle of deciding whether it is worth it to
go back to school and get a master's degree in computer science. I hope this
course will help me make that decision.

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Tichy
Any ideas what the actual schedule will be? Like specific times when new
videos go online, how much time will there be to hand in each exercise? I'd
like to plan my time... Same questions for AI-Class.

~~~
Benjo
There's an unanswered question on this in the class's internal forum:
<http://www.ml-class.org/course/qna/view?id=17>

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gnok
Somewhat disappointed after realizing that the videos are all in Flash. So I
can't watch this on my iPad. Does anyone know if these exact videos are also
available on iTunes U?

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bradly
Here are some download links:
[http://www.reddit.com/r/mlclass/comments/kgbsq/headsupagainn...](http://www.reddit.com/r/mlclass/comments/kgbsq/headsupagainnewest2011videosavailable_at/)

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gvkalra
The links on reddit are old (as clarified here: <http://www.ml-
class.org/course/qna/view?id=8>)

There is a work around to do this (am not sure how ethical this is). Since it
works am sharing the same.

1\. Disable Flash in your browser (preferably use FF) 2\. View video in HTML 5
mode (ex. <http://www.ml-class.org/course/video/html5embed?videoid=1>) 3\.
Right click on the video frame and select "Show only this frame" 4\. Right
click on the frame and select "Download with DownThemAll" ...

Required: DownThemAll FF addon ....

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yeison
Stanford rocks! The timing of this is so convenient. I started watching the
2009 lectures from Professor Ng's Machine Learning class just last week.

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mattdeboard
Just registered for this and looking forward to getting rolling.

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Tombar
It'll be cool if they provide a link to download video lectures, my internet
connection fails randomly and its hard to watch the videos smoothly ;S

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younata
Excellent.

It'll be interesting to see how this and the ai-class will affect my
performance in my other classes.

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wyclif
Anybody taking the databases class that starts on Oct. 10th?

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amirmc
See the spreadsheet at <http://bit.ly/pLCRzg>

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knarf55
Great news. Will be enrolling to check this out.

