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.