Subtitles section Play video Print subtitles 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.