13. Batch Normalization & LeNet, AlexNet Clothing Classifier/2. Build LeNet and test on MNIST.srt

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Hi and welcome the chapter to ten point one where we actually start building Linnett and Paris.

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So before we jump into Karris Let's actually talk a bit about that.

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That is quite old is quite an old CNN it was actually developed by lican.

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That's all it gets its name.

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Ellie.

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ELLIE.

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Sorry.

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And it was built in 1980.

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That's over 20 years ago and it was actually very very effective.

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On the amnestied a set in round writing didn't digit recognition.

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And you can visit this website to learn more about Lynette's.

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This is basically a sample example of how the net was constructed.

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This was the input convolutional is feature NOPs generated a convolutional layer some more maps and

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Celine's here as well.

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Disheartens was a map Max building here and building here.

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So let's look at Linette here in action.

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This was of.

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It's like a 20 year old program where we're actually using an inch and CNN and justifying these digits.

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So it is quite cool to see.

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So now let's jump into cameras and actually start building that hi and welcome to.

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I buy them a book.

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We're actually going to build Linnett and tested on that.

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So let's bring this up and I'm already seeing small Tipler right here.

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This should be in list.

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So basically we do our usual imposing images transforming all the It's a blah blah categorical one and

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puts all these things defining classes number of pixels.

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And now this here is Linette.

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It doesn't look like much does it.

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However this is the actual model that I just showed you those lights.

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Basically it has two sets of CERP which is basically convolution relo and pulling Dunhill then has a

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fully created layers and then basically we have all soft Max and all the usual optimizer.

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However we are using it a delta and create to model his only 1.2 million premises again and we train

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ticket Trinite on edness and see if it doesn't.

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And this latest model and these are the results.

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After 10 ebox and we can see it actually got quite good at ninety nine point twenty one percent that

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is actually really impressive.

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And if we go back to our presentation him this was let's bring this up right here.

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This was Lynley dance performance here.

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And I if you point one on this now that is CNN we used before of this what did he get.

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He got very close to Tony Potts as well.

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Nine nine point one five.

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But you can see 20 years ago CNN was designed this simple CNN here actually got such good results.

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I could imagine 20 years on hardware 20 years ago how long this would have taken to train do.

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And now it is we're using this on a tiny laptop but just you of course keep you and the trains within

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maybe half a mile.

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So that's quite impressive.

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Now let's move on to Alex net which is a lot more complicated than Linette.