
Machine Learning for Everyone - sneks
https://vas3k.com/blog/machine_learning/?ref=hn
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ultrasounder
Very nice write-up but most importantly very engaging visualizations which is
key to draw in the reader and keep them hooked. Can see how it will be useful
for someone who is coming in with nothing more than a few medium blog posts on
"AI for journeyman" and no prior experience or education that one would expect
to gain from a MOOC like Andrew Ng.

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andreyk
This is a pretty good overview, though rather hand-wavy (eg the overview of RL
here gives a VERY course idea of how this stuff works in practice). And the
characterization of existing similar overviews as either overly technical or
overly flimsy/fishy is a bit much ; this itself links to some things like
Machine Learning for Humans ([https://medium.com/machine-learning-for-
humans/supervised-le...](https://medium.com/machine-learning-for-
humans/supervised-learning-740383a2feab) , or see eg
[http://brohrer.github.io/blog.html#how_machine_learning](http://brohrer.github.io/blog.html#how_machine_learning))
, and in general as acknowledged by 'Yes, again' this is well trodden
territory. Still, nice pictures ; could make for a great video , perhaps.

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lhuser123
> As we can see here, this is obvious.

Funny and to the point. That’s kind of what I saw every time before. Now I’m
learning with Fastai, and feel like finally someone made it easy for the rest
of us.

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russfink
Because of the metaphor used in the opening sentence, I cannot assign it as
reading for my high school students. Too bad!

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mlevental
god forbid they read the word sex in school sponsored material.

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lern_too_spel
You don't see how it would be a problem for a teacher to assign reading
material about how he is having sex?

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mlevental
god forbid teachers have sex

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lern_too_spel
Nobody is saying they shouldn't. They shouldn't talk about their sex lives to
their students though, just like you shouldn't talk about your sex life to
your coworkers.

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king_magic
I’ve never seen genetic algorithms considered to be a subcategory of
reinforcement learning before.

> Genetic algorithms are considered as part of reinforcement learning

Uh, by who? Sure, there are similarities, but GAs != RL.

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Cybiote
I do not think the divisions so sharp. Many formulations in RL can be seen as
implicitly defining a particular (set of) differential equations. One can do
something similar for certain simple GAs and write them as equations of an
evolutionary game where stable strategies are good solutions to the objective.
The RL diff eqs also fall in this class.

Another view point is to note that John Holland, inventor of GAs, was more
interested in the application of GAs in classifier systems than as objects of
study in and of themselves. His work on the bucket brigade algorithm, a type
of TD-learning, for credit assignment in complex reinforcement learning
scenarios was first-rate and sadly still under-attended. In that setting, GAs
were a search operator, focused on exploration while bucket brigade was for
credit assignment. While GAs can be shown to be capable of doing adaptation as
well as exploration, they really were meant to be part of a bigger whole by
their inventor.

In fact, Deepmind's AlphaStar for Starcraft problem formulation can be seen as
fitting into the learning classifier system framework where learners are
themselves quite powerful neural networks. See:
[https://deepblue.lib.umich.edu/bitstream/handle/2027.42/2777...](https://deepblue.lib.umich.edu/bitstream/handle/2027.42/27777/0000171.pdf?sequence=1)

~~~
king_magic
> I do not think the divisions so sharp.

Yeah, I agree and see where they're coming from, just wasn't sure if both RLs
and GAs had been generalized into the same framework. Generalized to diff eqs
is interesting.

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esjeon
I love the first paragraph:

> thick academic trilogies filled with theorems ... or fishy fairytales about
> artificial intelligence, data-science magic, and jobs of the future.

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Chris2048
Is embedding a 3brown1blue vid ok?

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shinot
Brilliant and easy-to-read

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toxblh
Nice!

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vespertilio
awesome!

