
Course: Mathematics for machine learning - nafizh
https://www.coursera.org/specializations/mathematics-machine-learning
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icc97
This course is from Imperial College in London. It's typically ranked as one
of the top 3 universities from the UK. Finally it has joined the ranks of
doing a coursera course. Other noticeable absentees from coursera are Oxford
and Cambridge. I know they do provide a few of their own though open courses.

I guess universities shouldn't be forced to give open courses, but it is a
fantastic thing that US showed was possible and I hope that more UK
universities follow suit.

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argotechnica
Oxford actually has one course on EdX:
[https://www.edx.org/school/oxfordx](https://www.edx.org/school/oxfordx)

My understanding is that, like many MOOCs, it is largely department/faculty
driven rather than a strategic or philanthropic move by the university
overall.

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chi3
I've been looking for something like this to brush up/add to my math
knowledge; can anyone recommend this course or would you recommend some other
way?

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p1esk
Many ML methods require solid knowledge of probability and statistics.
Strangely this course does not cover that.

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geebee
My impression from reading about a few ML techniques (such as Neural Nets or
Support Vector Machines) is that this class of ML algorithms relies heavily on
regression techniques that are, at their core, nonlinear optimization
problems. This means finding local maxima and minima for systems of nonlinear
equations, either analytically or through gradient descent. Either way, you're
going to need to deal with a system of partial derivatives, which means you
need to understand vector calculus and linear algebra. If that's the focus of
this course, then I'd say it does make sense.

I understand what I described above is a subset of ML, and I generally do
agree with you that a solid background in probability and stats is important
for people who plan to do a lot of ML.

Note - another possible objection here is that _all_ "STEM" fields require
calculus through differential equations and linear algebra. That's pretty much
the common thread for most majors generally grouped together as STEM fields.
So calling this "mathematics for machine learning" could be a little strange.
If we're going to call vector calc and linear algebra "mathematics for ML",
why aren't we calling it "math for physics", or "math for engineering"... I
think that part of what is going on is that ML has gotten very popular, and
people are starting to ask what the essential math background is, and are
discovering that it's, well, pretty much the two year science and engineering
track calculus you'd take at most universities.

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p1esk
Funny, you used the term “regression”. People without stats 101 background
will not know what you’re talking about.

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thomasghjkl
Link is dead

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