My name is Joana Carrasqueira, and I'm a program manager

for TensorFlow.

Today, I'm very excited to bring you

the greatest and the latest about our community.

As you can see, our community is growing every day.

And here is a snapshot of the commits to TensorFlow

since we open sourced the technology in 2015.

Since then, our project has received 142,000 stars.

How impressive.

And we couldn't have gotten this far without you--

the community.

I'm truly impressed by all our contributions and hard work.

So thank you so much for all your efforts.

Now let's have a more in-depth look at the different groups

that form our community.

Our vibrant community includes code and non-code contributors,

community managers, and students.

But also we onboarded 148 machine

learning Google Developer experts

who are a part of the Google Developer Expert Network.

We also established 73 TensorFlow user groups

worldwide.

We formed 11 special interest groups and welcome

1,375 developers at the developers

at TensorFlow mailing list.

And just last year, we welcomed 20 students

at the Summer of Code.

Furthermore, our documentation has been

translated to 12 languages.

And on GitHub we have nearly 2,500 contributors

and nearly 9,000 commits.

How impressive, again.

What a fantastic work.

Altogether, we've built an open source project

that we can be very proud of.

I'm going to give you an overview

on how you can get involved in the TensorFlow community.

Firstly, the TensorFlow user groups,

they aim to upscale contributions

to TensorFlow with a local focus.

Some examples of the initiatives conducted by these groups,

they include events, meet-ups, and doc sprints.

The machine learning GDEs, they are experts and practitioners

from the community who support with outreach initiatives.

And finally, the Special Interest Groups, the SIGs.

They're focus groups contributing to TensorFlow

to certain parts in more specific projects.

Right now, we have 73 TensorFlow user groups distributed

all across the world.

And so far, these groups have reached more than 100,000

developers worldwide.

In your country, if you don't have a TensorFlow user

group yet, please feel free to reach out to us.

We can help you with the resources

and share best practices from other parts of the world.

These events are a great way to engage with other developers

and with the community.

We also strongly encourage students

to engage in these initiatives and learn with more experienced

developers.

After the TensorFlow roadshow in San Paolo

last October, we also established the first two

TensorFlow user groups in LATAM, in San Paolo, in Brazil,

and Argentina.

We are extremely happy to welcome these developers

to the TensorFlow community.

Also, in collaboration with our machine

learning ecosystem teams, we enable contributions

from the local communities.

And I'm very excited to announce that this year we

are going to do a series of TensorFlow bootcamps

and doc sprints in Latin America.

Our goal is to really get closer to you, to the machine learning

and the TensorFlow communities.

So we look forward to stay connected

with the communities in Colombia, Argentina, Chile,

and Mexico.

Documentation is also the backbone

off an open source project.

And so far, we have 268 tutorials and notebooks

translated across 12 different languages.

Additionally, we have over 40 translation

pull requests that are still awaiting review.

We really want to provide a good experience to our contributors.

And in order to achieve this goal,

we'll continue to support translations

of our documentation into several different languages.

Just last year, the machine learning GDEs,

they gave more than 100,000 talks.

And they published 295 articles that reached out more than half

a million developers.

Our machine learning GDEs, they play a critical role

in advancing machine learning education worldwide.

And if you'd like to be a part of this brilliant group,

please get in touch with us.

Just to highlight a few events where our machine learning GDEs

spoke at last year.

We have a few pictures, as you can see here,

and they refer to the African Build

Up Event, the Explore Machine Learning India Day,

and the doc sprints in Korea.

For bigger projects in which we have to work as a team,

we created the TensorFlow Special Interest Groups.

This is a program that organizes contributors into focus stream

areas of work.

These groups, they take ownership of specific areas

to add and maintain new features to TensorFlow.

It all started with a SIG build.

And right now, we have 11 different SIGs.

The contributors are welcome to join the SIGs

based on the parts of TensorFlow that they care the most.

As I mentioned before, our ecosystem

includes the SIG add-ons, Build IO, Networking, JVM, and Rust,

and Micro, who are community-led open source projects.

Whereas Keras, MLIR, Swift, and TensorBoard

are Google-led with an open source philosophy.

Each individual SIG meets on a monthly basis.

And if you want to be part of a SIG,

you can head to GitHub for more information on how to join.

You can also request a new SIG.

And we are here to help you and guide you through the process.

There are many ways that you can contribute to a SIG.

And these are just a few examples of specific projects

that are looking for contributors in 2020.

A great way to get feedback on a large project

is through the request for comment or RFC process.

It is the primary way we communicate our design

rationale and receive feedback from the community.

Anyone can create or comment on an RFC.

We have started tweeting our RFCs.

So please, keep an eye at the TensorFlow Twitter account.

We manage our RFC process on GitHub.

And there you can comment on an open RFC or propose a new RFC.

If you want to propose a design, we strongly

encourage you to socialize your idea, recruit the sponsor,

write your RFC, respond to feedback, and implement it.

And if you are interested in learning more about TensorFlow,

you may want to consider doing one

of our fantastic online courses, either on Coursera or Udacity.

We are proud to also announce that our university

program includes new courses about TensorFlow

at MIT, Imperial College, and University of Hong Kong,

just to mention a few.

And lastly, as announced this morning,

we are launching the TensorFlow Certificate Program.

It is intended for individuals who

want to advance their deep learning proficiency

and want to demonstrate experience

in building practical business applications using TensorFlow.

Head to tensorflow.org/certificate

for more information.

And then lastly, please follow us

on social media for the latest news

and content about TensorFlow and the community.

On Twitter, you can get the latest news about TensorFlow.

Head to the blog for more technical use cases

and best practices.

And then our YouTube channel has more educational resources

that will help you through your journey.

Get in touch and get involved with the community.

Thank you so much.

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