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I've been doing machine learning for a long time, and
it's a really exciting time to be doing machine learning today,
because we're really seeing a lot of impact from it.
But this is not how I started machine learning.
If you just talked to me a few years ago,
the way I thought about machine learning was quite different.
You started with some data sets, some data.
And you fed it to some magical machine learning algorithm and
then I just showed you that my curve was better than your curve and
then I wrote the paper to machine learning conference.
And that's how I always thought about machine learning.
But this is not why I got into the first place,
why did I get into machine learning?
Now when I was a kid I read a lot of books.
A lot of sci-fi.
You know I really wanted to build robots that were really intelligent that
really thought about the world and
reasoned about things, what I call today intelligent applications.
And the really cool and exciting thing is that today we're seeing a lot of
impact from intelligent applications, they're using machine learning.
In fact if you look at English industry successful companies today.
Companies that are called disruptive, they take a market and completely change it.
They're often differentiated by intelligent applications,
by intelligence that uses machine learning at its core.
So, for example, early days Amazon really disrupted the retail market
by bringing in product recommendations into their website.
We saw Google disrupting the advertising market by really targeting advertising
with machine learning to figure out what people would click on.
You saw Netflix, the movie distribution company,
really change how movies are seen.
Now we don't go to a shop and rent movies anymore.
We go to the web and we stream data.
Netflix really changed that.
And at the core there was a recommender system that helped me find the movies
that I liked, the movies that are good for me out of the many, many,
many thousands of movies they were serving.
You see companies like Pandora, where they're providing
a music recommendation system where I find music that I like.
And I find streams that are good for the morning when I'm sleepy or
at night when I'm ready to go to bed and I want to listen to different music.
And they really find good music for us.
And you see that in many places, in many industries,
you see Facebook connecting me with people who I might want to be friends with.
And you even see companies like Uber disrupting the taxi industry by really
optimizing how to connect drivers with people in real time.
So, in all these areas, machine learning is one of the core technologies,
the technology that makes that company's product really special.
So in this specialization, we're really going to talk about all aspects of machine
learning and get you ready to build intelligent applications just like that.
And we're gonna see a pipeline again, and again, and
again where we're gonna start from data and really bring in a machine learning
method that provides you with a new kind of analysis of the data.
And that analysis is gonna give you intelligence.
Intelligence like what product am I likely to buy right now?
And by taking this pipeline and working through it in a wide range of settings and
a wide range of applications, with a range of algorithms, but really understanding
how they connect together, you're gonna be able to really build smart,
intelligent applications of your own.
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