Neural Network is one of the most
used algorithms, but it's
getting popularity with this.
What is actually inside.
So we have some of the, well, this
project using new release that is
optic detection, basic organization
image classification, thanks to speech
and Google companies like Instagram,
Twitter, Google, apparently using.
So let's tell you what actually
just to classify between then
why you should go for using.
Right.
So basically in the traditional
machine learning, you need to do
manual selection of the features,
but for the deep learning, deep
learning, deep learning, you don't
need to go from manual selection.
Your model will automatically select
the feature, which is actually required
to classify picture for platform.
What is eat actually is a network on
the circuit of a neural network is
either a biological NEDA noodle or real
biological neurons, or an artificial for
solving artificial intelligence problems.
But then it should have been
biological noodles and modeler.
As
connections, negative values
mean inhibitory connections.
All inputs are modified by this activity
is referred to as a linear function,
controls the amplitude of the, that.
For an example, range is
usually between zero and one.
It could be minus
network is an interconnected
group, natural artificial
mathematical or computational model.
Data modeling or decision making.
You don't need what sauce
between inputs and outputs or
to find patterns in that data.
Bye.
At the university, Chico, what we have
the basic components of biological
input, activations, or output as a
series of brief action punches, the
numeracy body process, the incoming
activation activations, the numerous
nucleus contains the genetic material.
Well, most this exists
in most types of no, just
reach innovate from the sale.
Bobby Jones activation from other.
activation activation.
Other the junction said a little
signal transmission between the
accents and the Dean writes.
Of course, the process of
transmission is by diffusion
of chemical neurotransmitters.
Let's have a look.
Human brains versus the new
building, the human brain.
We have been right cell body,
some terminal, but you work.
We have activation function.
We have.
That's right.
So what we have, we have the integrator,
we have hidden layers and we have
having human rights versus
new in the human brain.
We have seen nucleus artificial.
You don't have, we have in the
artificial neural network, we have
input like it's on its way street in
new lawn, the human brain that's in the
noodle, interconnections in Mandarin.
We have that sense that in
the neuro Lake, we have the
mapping on activation function.
That is April.
And lastly we have in
the human being that is.
I'm in the noodle network.
We have output that is, let's have a look
at what is some limited number of inputs.
Some weeks is tied to each of this and
the noodle simply text some carries
out a weighted summation office.
So this is how, what actually knew them.
That is our position.
We have vegan bias.
We have made some activation
Allstate function.
So what happened actually give your image.
So your image will be
converted as an input.
Right.
So after that, that inputs
will be weighted some bias
to pass those.
And then last week we did well.
Okay.
Now let's have a look
running best on the network's performance.
On example classes correctly,
which contributing to the increased
activation function, the Activision
sanction out of that note status
integrated it's like it can
be seen as a digital network.
Activation function that can be on
or off, depending on this is what
actually activation functions,
activation function.
So we use the function.
We use heart function.
We use softmax function function.
We also use rectified media
unit that is known as lastly,
we use exponential linear units.
You lose function.
So we almost came to an
end of the shot video.
I hope you guys like it.
Always wanting to know more, this
then piece of site, grade learning,
if you want to actually,
yeah, please go to
you continue your certificate as well.
Johnny app on the mobile
application that is also available.
Thank you so much.
