Kind: captions
Language: en
[Music]
so what advice do you have for someone
who wants to get started in deep
learning train lots of models that's
that's how you that's how you learn it
so like so I would you know I think it's
not just me I think I think our course
is very good but also lots of people
independently is that it's very good it
recently won the cog X award for AI
courses as being the best in the world
so let's say come to our course cost up
faster day I and the thing I keep on
harping on in my lessons is train models
print out the inputs to the models print
out to the outputs to the models like
study you know change change the inputs
a bit look at how the outputs vary just
run lots of experiments to get a you
know an intuitive understanding of
what's going on to get hooked do you
think you mentioned training do you
think just running the models inference
like if we talk about getting started no
you've got to find true in the models so
that's that's that's the critical thing
because at that point you now have a
model that's in your domain area so
there's there's there's no point running
somebody else's model because it's not
your model like so it only takes five
minutes to fine-tune a model for the
data you care about and in lesson two of
the course we teach you how to create
your own data set from scratch by
scripting google image search so and we
show you how to actually create a web
application running online so I create
one in the course that differentiates
between a teddy bear or grizzly bear and
a brown bear and it does it with
basically hundred percent accuracy took
me about four minutes to scrape the
images from Google search in the script
there's a little graphical widgets we
have in the notebook that help you clean
up the data set there's other widgets
that help you study the results to see
where the errors are happening and so
now we've got over a thousand replies in
our share your work here thread of
students saying here's the thing I built
and so those people who like and a lot
of them are state of the art like
somebody said oh I tried looking at
different gary characters
couldn't believe it the thing that came
out was more accurate than the best
academic paper after Lesson one and then
there's others which are just more kind
of fun like somebody who's doing
Trinidad and Tobago hummingbirds she
said that's kind of their national bird
and she's got something that can now
classify Trinidad and Tobago
hummingbirds so yeah train models
fine-tune models with your data set and
then study their inputs and outputs
how much is fast their courses free
everything we do is free
we have no revenue sources of any kind
it's just a service to the community
you're a saint
okay once the person understands the
basics trains a bunch of models if we
look at the scale of years what advice
do you have for someone wanting to
eventually become an expert train lots
of models train lots of models in your
domain area so an expert what right we
don't need more expert like create
slightly evolutionary research in areas
that everybody's studying we need
experts at using deep learning to
diagnose malaria well we need experts at
using deep learning to analyze language
to study media bias so we need experts
in analyzing fisheries to identify
problem areas and you know the ocean you
know that that's that's what we need so
like become the expert in your passion
area and this is a tool which you can
use just about anything and you'll be
able to do that thing better than other
people particularly by combining it with
your passion and domain expertise so
that's really interesting even if you do
want to innovate on transfer learning or
active learning your thought is it means
one i I certainly share is you also need
to find a domain or data set that you
actually really care for right if you're
not working on a real problem that you
understand how do you know if you're
doing it any good you know how do you
know if your results so good how do you
know if you're getting bad results why
you're getting bad results is it a
problem with it
like how do you know you're doing
anything useful yeah the only to me the
only really interesting research is not
the only but the vast majority of
interesting research is like try and
solve an actual problem and solve it
really well
you