
Artificial Neural Networks – Introduction - rzagabe
http://www.rzagabe.com/artificial-neural-network-introduction/
======
daveid
This was a really nice article but I was anticipating more (an implementation
example) at the end of it, hope you'll add more to it later!

------
maskedinvader
The following quote from the author: "Our brains behave like monkeys and it
can be proven that most of our lives are about "what am I going to have for
lunch?"..."

has this been proved ? would be very interested to know who proved this and
how they went about doing it.

~~~
rebootthesystem
> has this been proved ?

Yes!

> would be very interested to know who proved this and how they went about
> doing it.

Well. There's this thing you do. It only takes a few minutes. Then you wait
about nine months. At that point you start collecting data. The first year or
two are somewhat inconclusive. The data (and the subject) can be very noisy.
By the time you've made observations and collected data for about eight years
the conclusion is inescapable: Monkeys.

According to my observations across three of these experiments I would add
that monkeys might sometimes have an edge over some of the crap we pull.

------
a-priori
Take all arguments that these models resemble our brain with a huge grain of
salt. At best they're a metaphor.

There's one critical difference between biological neural networks and the
artificial models they're talking about here: the biological neurons produce
spikes when they activate, not continuously-variable activation levels.

These artificial models whitewash these features away by modelling only the
neuron's firing rate and not the inter-spike timing or spike train behaviours.

------
SiVal
_There is this interesting paper titled “A Few Useful Things to Know about
Machine Learning”, which basically ..._

That link leads to the Japanese toilet maker Toto, not to any ML paper. I
suspect it was pranksters, not the author.

------
bearzoo
The brain has no objective function it is trying to minimize

~~~
rzagabe
> Keep in mind that ANNs aren't about duplicating human brains and that a lot
> of aspects already don't correlate with our current, very short,
> understanding of them (i.e. learning algorithms, backpropagation,...)

> We'll see that artificial neural networks are not that different from our
> magnificent biological system "in their most basic definitions".

I've tried to make it clear enough that we should avoid analogies with
biological neural systems.

