So welcome to a brand new module this module is going to be pretty jam packed with some pretty cool
stuff as well.
So what's coming up in the previous module.
We introduced the multilayer perception.
And it didn't really do all that well on the classification task but it was given.
So this time round we're gonna give it another chance.
We're gonna see how it does.
On a different dataset what data set is that.
Well it's gonna be a data set of handwritten digits the so-called enhanced dataset.
My motivation for continuing on with the perception is that we get to understand it on a deeper level.
And we also can learn some proper tensor flow along the way.
And when I say proper tensor flow I mean taking off the caris training wheels and looking under the
hood we're gonna be getting our hands dirty with the tensor flow graph tensor flow sessions forward
tensor baud goodness.
And yes you guessed it tenses for this module are going to be running everything locally on my machine
but you can also follow along in the Google collab notebook the architecture that I'm going to be proposing
for our neural network is not going to require a GP you it's not gonna be too demanding but depending
on your machine and if you do need more juice or you want to experiment with a more demanding version
of the perception then Google cool up notebooks and their free GP runtime is gonna be your friend.
So if you need the juice go with the Google cool lab notebook and if you'd like to see what's going
on with tensor board and we're going to be working a whole lot with tensor board in this module then
run everything locally.
Now without further ado let's get set up and let's get started.