What does it take to download
a public dataset off the Internet,
like cats verses dogs,
and get a neural network to work on it?
Data is messy, sometimes
you find surprising things like pictures of
people holding cats or
multiple cats or surprising things in data.
In this week, you get to practice
with using TensorFlow to deal with all of these issues.
Yeah, and it's like, so even for example,
you might have some files that are
zero length and they could be corrupt as a results.
So it's like using your Python skills,
using your TensorFlow skills
to be able to filter them out.
Building a convolutional net
to be able to spot things like you mentioned,
a person holding it up.
So that's some of the things we'll
do this week, is by using,
and it's still a very clean dataset
that we're using with cats versus dogs,
but you're going to hit some of those issues.
I think you'll learn the skills that you need to be
able to deal with
other datasets that may not be as clean as this one.
Yeah. Sometimes people think that
AI is people like Lawrence and
me sitting in front of
a white board maybe a zen garden outside,
talking about the future of humanity.
The reality is, there's a lot of data cleaning,
and having great tools to help with
that data cleaning makes
our workflow much more efficient.
Definitely.
So in this week,
you get to practice all that,
as well as train a pretty cool neural network
to classify cats versus dogs. Please dive in.