
Ask HN: Recommendations for ML training 2h a week - erebrus
The company where I work has allowed me to pick up training up to 2h a week on a subject I like. I would like to pick up AI, probably more the ML part and I&#x27;m wondering what would be the best way to make the most of my time.<p>Just researching on myself is not out of the question, but something a bit more structured would be better. Still, 2h a week might be a bit too little to spend following a proper AI class online.<p>Also, I&#x27;m not new to the subject, but I haven&#x27;t really done much in it in over 10 years. Therefore, a normal introductory course might be somewhat useless in some points but required in other points. As such, something that I can choose the pace would be the most appropriate.<p>Any recommendations would be very much appreciated...
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brudgers
Just a thought: is it practical to match the company time with some of your
own time? e.g. two hours of company time plus two hours of your own time. The
degree to which that sounds like a good idea might be a useful way of gaging
your own interest in a particular method or course of study...material that is
engaging enough to pursue outside of work is likely to be a good choice _for
you._

A second thought is to frame the project in calendar time. Two hours a week is
a lot of hours over a year.

A third thought is to frame the project in workday time. A half hour a day,
every work day is a steady discipline.

Finally, I'm biased toward beginning at the beginning because I often find
that skipping the early basics based on what I know means I miss the author
telling me which basics the author thinks are important (and since they're the
expert, perhaps I ought to value their judgment a bit more than my own in that
regard).

Good luck.

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boniface316
I am taking Machine Learning on coursera by Andrew Ag. Initially I was
intimidated by the idea of ML as I had no prior programming experience. I
started learning data science stuff less than 6 months ago. I started to feel
motivated and confident about ML by taking this course. I highly recommend it.

[https://www.coursera.org/learn/machine-
learning](https://www.coursera.org/learn/machine-learning)

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erebrus
Thanks. I'll look that up. However, how much time does that takes you
(weekly)?

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mindcrime
It's self-paced, so it's kinda up to you. There are "deadlines" to help keep
you on track, but they're optional. To pass, you just have to pass all the
graded assignments by the end date. But if you're getting close to the end and
are behind, you can always shift your enrollment to the following session -
but you keep all your progress and everything. It's pretty cool in that
regard. Very low pressure.

~~~
erebrus
That's cool. Can you tell me how much time you spend on it per week in
average? Just so I get a general idea...

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mindcrime
It's been a while since I took it, but I think I spent an hour or two a week
watching the videos and reading notes and whatever, and then maybe another 3-5
hours on the programming assignment. It was probably less than that on the
earlier programming assignments, and more on the later ones as things got more
complicated later on. And I might have spent more time on the videos on
certain sections, because of re-watching sections that weren't intuitively
clear to me right away. In particular, some of the math'ier stuff where he
explained the stuff about using partial derivatives to calculate the error
gradients for neural networks... that stuff I had to put more work into since
my math background isn't real strong (I never took multi-variable calculus).

All of that said, you can get through the class and learn and understand the
material at the level he teaches it, even without completely understanding
partial derivatives (a point he makes in the lecture). But having a strong
calculus background certainly wouldn't hurt.

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mindcrime
If it isn't too introductory, I'd say take the Andrew Ng course on Machine
Learning on Coursera. If that's too introductory, try the Geoffrey Hinton
course on Neural Networks on Coursera, or the Google / Tensorflow course on
Deep Learning on, er, I think it's EdX.

