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  • JOANA CARRASQUEIRA: Welcome, everybody.

  • It's an absolute pleasure to be here with you today.

  • As Jocelyn mentioned, I'm Joana Carrasqueira.

  • And I'm a program manager for TensorFlow at Google.

  • I'm joined by my colleague Nicole Pang.

  • NICOLE PANG: Yes, I'm Nicole.

  • I'm a product manager for TensorFlow at Google.

  • JOANA CARRASQUEIRA: And we're going

  • to talk about the TensorFlow community

  • and the many exciting ways by which you can get involved

  • in the work that we do.

  • So let me start by saying thank you.

  • Thank you to you, thank you to the community for all

  • the hard work that you've done.

  • Since we've open-sourced TensorFlow in 2015,

  • we've received so many contributions and so much

  • support from the community that really the project, where

  • it is today, is due to you, to all your efforts

  • and all your hard work.

  • So thank you for that.

  • Just on core TensorFlow alone, we've

  • received more than 6,000 commits from over 2000 contributors.

  • This is so impressive.

  • But not just only this.

  • On Stack Overflow, we have received

  • more than 50,000 questions.

  • And we have onboarded more than 120 machine learning experts

  • through our Google Developer Experts program.

  • And we have established 50 user groups all around the world.

  • We've also had 25 guest posts on our TensorFlow

  • blog, which is fantastic.

  • And our community only continues to grow.

  • Here is a snapshot where you can see

  • that the number of commits from four years ago

  • has been rapidly growing.

  • And there's so much support and excitement from the community.

  • We truly couldn't have gotten this far

  • if it wasn't for you, for the contributors, for all

  • the work that you do.

  • So thank you so much for that.

  • NICOLE PANG: And it's not just the contributions you see

  • and the feedback we get from our community on GitHub and Stack

  • Overflow.

  • But of course, as you all know, TensorFlow

  • has a global world-wide community.

  • And we see a lot of love for TensorFlow

  • also on other avenues.

  • You probably have heard a lot about TF 2.0 today, yesterday.

  • And you certainly will hear more about it tomorrow.

  • But TF 2.0 is one instance where our global community responds

  • really positively.

  • And we see so many cases of that.

  • And today, we'll touch on these cases and, of course,

  • how you can get involved in our communities.

  • So briefly, what we'll talk about today.

  • We want to tell you how you can learn TensorFlow,

  • how you can get started in your own journey of using

  • TensorFlow, whether you're more in the beginning stages,

  • or you're really advanced user of TensorFlow

  • in your applications.

  • Then we want to showcase to you our global community, really

  • run through some really amazing use cases,

  • really tell you what we've seen people do with TensorFlow

  • or people use TensorFlow for.

  • And hopefully, that can be very inspirational for all of us

  • in the community.

  • And, of course, why you're here today--

  • you want to know how to get involved at TensorFlow.

  • So we'll walk you through not just the ways that you might

  • first think of, which might be contributing code

  • because TensorFlow is open source, but also

  • a lot of community groups, a lot of special interest groups.

  • And those, again, are all over the world.

  • So both for everyone here in this room and, of course,

  • everyone watching online, there's many, many resources.

  • And we're so excited to share with you.

  • JOANA CARRASQUEIRA: So as you could see,

  • we truly have a vibrant global community

  • that continues to grow because there's

  • so much that you can do, so much that we can all

  • contribute to TensorFlow.

  • And let's have a look at where our community is phased,

  • and what they're doing right now.

  • So the TensorFlow user groups, they

  • are a wonderful way of getting involved with TensorFlow.

  • Either online or face-to-face, you

  • can meet with other like-minded contributors and developers

  • really to answer questions, to solve problems, challenges

  • and building those use cases on really

  • how you can implement TensorFlow across different industries.

  • So just an example--

  • one of our user groups in Korea.

  • That one is the biggest that we have in the world.

  • And we have engaged more than 46,000 members.

  • It is very impressive.

  • And in China alone, it's the country with most user groups.

  • And they have user groups across 15 different cities.

  • It's really impressive how the community is growing so fast

  • all over the world.

  • And one of the key messages that Nicole and I would

  • like you to retain from our presentation today

  • is that if you don't have a user group where you're

  • based or in your region, feel free to start one,

  • share your experiences, connect with

  • other like-minded developers, and start

  • talking about TensorFlow.

  • We are here to support you throughout this process

  • and this journey.

  • So feel free to reach out to us.

  • We're very happy to guide you through the process.

  • And like I mentioned, if you would

  • like to start your user group, here are

  • some of the resources that you can have a look online

  • if you are interested in starting your own group.

  • We also are sharing our alias, so you can really

  • get to know the team and how you can

  • start creating your user group.

  • NICOLE PANG: So in the spirit of honoring our global community,

  • we want to briefly touch on what the TensorFlow

  • team has been doing worldwide.

  • So like Joana just said, we have so many user groups.

  • And you really can see that they are global.

  • And as you heard this morning in the keynote,

  • the TensorFlow team was really excited

  • and really lucky to be able to go to many cities,

  • and meet many of these users, and meet many of the companies,

  • and meet many of the startups that

  • are using TensorFlow in so many different cities in the world.

  • And, of course, we're so excited that you're here today,

  • on one of our stops on the TensorFlow

  • roadshow in Santa Clara today.

  • And we're really, really excited to, again,

  • be able to see the use cases.

  • And we'd love to share briefly some

  • of these use cases with you.

  • So first off, when we look at Asia and Asia Pacific,

  • there's a really big, vibrant community there.

  • And as Joana just said, a lot of people in Korea,

  • a lot of people in India, a lot of people in China,

  • they're all using TensorFlow with two amazing applications.

  • So in China, for instance, TensorFlow is actually not

  • just active on our applications, but also the community

  • is really active on our official TensorFlow WeChat channel.

  • And this WeChat channel showcases

  • a lot of use cases of TF Lite on mobile.

  • Like you can see this one example of a video platform

  • called IT with image segmentation on mobile devices.

  • So again, they're doing really awesome work.

  • And not just doing awesome work but also

  • sharing with all of the community on the WeChat blog.

  • And we're really, really glad that we're partnering with them

  • and really glad to see these use cases come up.

  • JOANA CARRASQUEIRA: Yes, and Nicole and I

  • were really fortunate that we were able to join the roadshows

  • and really connect with the local communities worldwide.

  • So for example, at the roadshow in Latin America,

  • we connected with ALeRCE, which is a startup in Chile.

  • And they are trying to detect supernovas and galaxies

  • through the [INAUDIBLE] of child processes and machine learning.

  • And this was really cool.

  • And they used conventional neural networks

  • to classify astronomical objects contained

  • in a stream of about 200,000 images per day.

  • The work that they're doing is so impressive.

  • And it's absolutely worth sharing

  • with the rest of the community.

  • Another example-- in Europe, we connected

  • with EyeEm, which is a library of photos that uses TensorFlow

  • for object classification.

  • And their algorithm scores photos

  • based on their static quality but also on the relevance

  • to your brand's visual identity.

  • And then every photo is automatically tagged

  • with keywords just to make sure that the entire library is

  • searchable.