>> Hello, my name is Noelle LaCharite and welcome
to another episode of This Week In Cognitive,
where we are going to talk
through all the different ways that you can learn by
doing with Cognitive Services and
really a bunch of different things in Microsoft AI.
So first, I always like to remind you of some of
the pre-built models that are available at your disposal.
Some of our other episodes have
talked through this in more detail,
so feel free to go back and take a look at those.
But today, we're going to take
a look at a bunch of different samples.
All the different ways that you can,
across different properties in Microsoft AI,
learn by implementing projects
that had been built by other engineers and shared with you.
These are available all over the place from GitHub,
to different galleries within Microsoft,
and so I'm going to just take a few moments
and share those with you.
So, the first stop on this tour of all the things you can learn
by actually building projects yourself is inside of our samples.
If you go out to GitHub,
and you'll see this link in the description of the video.
But if you go to GitHub, you can go to
Azure samples and in this organization,
you will see a ton of samples.
We want to actually refine the search a little bit.
So, I would have you go in and type in "Cognitive Services."
Once you have "Cognitive Services," you'll
see a bunch of specific samples show up.
I will call your attention.
Remember in a previous episode,
we talked about using speech-to-text and
text-to-speech to you're see these projects there,
but I'm actually going to show you a couple very specific ones
that my team has created and I'm super excited about.
One is called Studybot.
Now the Studybot sample, and you'll see it here,
it's in C# that we're working on building it
across all of our primary languages.
But this sample allows you to go and just see
a typical rather complex combination of
Cognitive Services that are built in order to
create a standard intelligent agent.
If you're looking for an example that you can go
and just take this code and start from there.
You know a lot of times,
we suffer from my blank space or blank page syndrome, right?
Where we're like, "Oh my gosh, how do I even just get started?"
So, these projects are built for exactly that purpose.
We have found, based on a lot of the data that we've gotten,
that customers are looking to build intelligent agents.
So, this is an incredibly useful skill for
you to develop and you can do that just
by building some of these samples,
and diving into the code,
and all of that code is available here.
A lot of our samples, you'll also see,
they come with a nice ReadMe file
that'll tell you how to use the sample,
what's in each folder,
and some descriptions are on what we did and what we tried to do.
Now remember, these are samples so they're not meant to be
the golden use case of how to do everything.
It's just a chance for you to get started quickly,
build something meaningful and something that
you can translate to the enterprise.
So, another example of services I wanted to also show you,
can be found in AI School.
Now AI School is more like a training curriculum, right?
Your ability to go in and take some classes.
There's lots of different ways to do this.
Some of them are Cognitive Services so if
you wanted to really dive deep and get
a full blown application development experience
in using Cognitive Services or Cognitive Search or bots,
you can actually build an intelligent agent or
build a Computer Vision application
all within the context of some of these courses.
They are much longer, right?
With some of these samples, you can just go to
Github,clone the repo and get going right away.
These are a little bit longer,
they're usually hours of time invested.
But the benefit of that is that you are handheld a
little bit more than you would be with a GitHub repo.
You're also provided the step-by-step guide,
and then on top of that,
it usually is much more in depth, right?
We go through multiple scenarios within a single class.
So, a really great opportunity
for you to go and take a look at it.
You can see some of
these applications are built out like Conversational AI,
huge opportunity in our industry right now.
Every company is looking for ways to build
Conversational AI into the applications that they have,
but you also see machine-learning and
intelligent edge. All things, right?
Worth your investment.
Dive into it, start building.
If you feel super comfortable in it,
maybe you can just build a sample from GitHub,
but if not, if you need
a little bit more guidance or maybe a lot more guidance,
these classes will help you.
Now another thing, another area
when I found it I was like, "This is incredible."
I think some of you might remember that I had shared
with you the architecture of Microsoft AI, right?
Sometimes, we want to use pre- built models and actually,
anytime we can use a pre- built model, we want to do that.
But then on the other side,
there are some problems that
we really need to build our own model for, right?
We want to maybe build something that no one's ever built before.
Built-in in a way that's very
very specific to our business or industry.
So, machine learning allows us to do
that and the gallery which I am showing to you now,
allows you to see project examples
that are built already that you can, again,
allows you to start rather than from scratch,
you can actually start with an existing project.
So, if you go in here,
one of the nice things I like about it,
which I want to just point your attention to,
is that you can search by industry.
So, our goal as Microsoft and
as the engineer's building the samples for you,
is to fill up each one of these buckets, right?
Retail, manufacturing, banking, health care,
how can we make it easier for you to get started?
So, we're looking to build scenarios,
place them in here.
Whether they're using pre-built models,
which you'll see those in
our samples and GitHub and maybe in the AI School,
or for the machine learning models you're building from scratch.
We will build these AI Galleries right
up projects within the gallery that allow
you to start with a model that
will speed up your ability to develop something.
Now, there's lots of opportunities you'll see here on this page.
There's tutorials that you can download,
that'll walk you step-by-step
through building a model from scratch.
Or you can take an existing model and just
augment it if you're already
experienced in how to do it step-by-step.
So, we try to meet you where you are,
where your experiences in order to give you
the full breadth of learning, right?
I am a huge fan of learning by doing, I think.
If you can build a bunch of samples and create
some muscle memory around either creating a model,
or using a pre-built model or
a collection of pre-built models together,
that's how you're really going to be able to impact your business.
So, I really encourage you in order to start building immediately,
now you've got some pretty decent tools
The last one I want to show you is
where some of our most fun projects are.
You'll remember this from some of the things that
we've done in the past, right?
We have the AI Lab.
AI Lab is home to the JFK Files
which we've seen before and you probably have seen on the AI Show,
but it's also home to a bunch of other cool projects.
The reason that I love these projects,
is that kind of a philosophy of mine is if I demo something,
if I go on stage or if I
demonstrate in a hackathon how to do something,
I want to make sure there's a GitHub Repo to back it up.
That the source files are available to you as a def.
So, you can see here.
Look at all these really cool projects these
are Snip Insights one of my favorite.
Sketch to Code, right?
So, one thing that I do a lot as I stand up in front of people and
explain to them the architecture of Microsoft AI,
and I always would drive that drawing would get lost.
Today, I can now draw it
and sometimes I'll use a Surface Hub, right?
Draw it on a board and then I can
instantly have that generated into
HTML and have a webpage or
a graphic that represents that that I can reuse.
It's incredible. But what's most incredible about it is that,
that source code is available to me.
So now, I can even integrate that into my applications,
I can access it,
I can add on top of it,
I could even contribute to the project if I want to.
What an awesome opportunity, right?
Something that we all want to try and do.
So, you'll also see here Building a Bot,
right? Drawing Bot, Drones.
This list of projects just grows and grows,
there's teams that are just dedicated to building innovative,
fun projects in the AI lab for you to learn from.
So, do it. Take a look, right?
I've shown you three really interesting areas
to focus on in order to learn by doing.
One is in our GitHub repos,
there's tons of samples in there Think about
your business problem and then go searching
for it within the context of those samples.
Then, second place is to go and actually take maybe
some more formalized classes, right?
So, if you want to take a formalized class,
you could do that in AI School.
Then, if you're looking for something that's
not just in the box of
pre-built AI or not just
within some of the models that you would customize,
but instead you want to build your own model,
we have a whole gallery of helper projects and
models that you can leverage in
order to speed up your development process.
Then finally, as you just saw, right?
So much fun happening in the AI lab projects that really
are extremely inspiring to
look at but more importantly have the source.
So, you can go in, grab
the source and get started with a cool project.
So, hopefully, you've enjoyed today's episode.
It's just all about the things that you can dive into.
We'll be spending future episodes going into each one of these,
pulling out a specific project and getting started.
So, I thought it'd be really great if you had
an opportunity to take a look around these sites first.
So, thanks very much for joining
us and I'll see you on the next episode