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Congratulations on
coming to the end of

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this TensorFlow and
practice specialization.

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In the four courses,

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you learn how to build
a deep neural network,

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how to build a comf net,

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how to build sequence models
for NLP and finally,

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how to build time series models.

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You've built and
you've learned a lot

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of stuff in the specialization,

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and I hope you give yourself

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a pat on the back for
getting to the end.

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We've really come a long way,

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if you remember our very
first lesson is we did

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two sets of numbers where

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the relationship was
y equals 2x minus 1.

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We had a little DNN

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that people use then
to learn that and

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to do that pattern
matching of the x

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against y, but since then,

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we've gone into computer vision,

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natural language processing,
time sequence modeling,

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sunspots, all that thing.

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So I really think that
you've really just

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taken the first step though
on a much bigger journey,

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there's so much more
stuff to learn.

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One of the pieces of
feedback that we get from

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students is that they
really love this,

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but they want to learn more.

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I always recommend that
the other specializations

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that Andrew has done that I've

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personally learned from as well.

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So if you really want to go into

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more depth into for example,

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how an LSTM works or
how an RNN works,

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or how even a convolution works,

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there's some great
material out there,

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and we've designed
these materials

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to mesh with each other.

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So if you really want to learn

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in-depth, Andrew is the master,

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and if you want to
learn how to then apply

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that to code and
how to take that,

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and put it into practice,

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then this course and
future courses that

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we're working on will be
really all around that.

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So we hope to see you there.

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As Lawrence said, I hope
this is just a part of

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your journey to become
great at deep-learning.

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The deep learning specialization
compliments this one,

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and so if you want to
go into greater depth,

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you can check that out too.

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There's still more to
learn. So Lawrence and

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I are still going
to be continuing to

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build additional
specializations to

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help you learn even
more about TensorFlow.

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Looking forward to it.

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Working with Lawrence has
been the highlight of

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these past few months and I look

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forward to building
more courses together.

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To all of you that stuck

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with us throughout
all this period,

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thank you for
all the hard work you put

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into learning these things
and keep watching the space,

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we'll have more things
for you in the future.

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Thank you.