Posted by Joana Carrasqueira, Developer Relations Program Manager

Thank you to everyone who joined us at the second Women in Machine Learning Symposium!

Last year we founded the Women in Machine Learning program, with the goal of building an inclusive space for all intersections of diversity and to give a voice and platform to women passionate about ML. Hundreds joined to share tips and insights for careers in ML, learned how to get involved in the community, contributed to open source, and much more.

This year, thousands of ML practitioners joined from all over the world. Everyone came together to learn the latest Machine Learning tools and techniques, get the scoop on the newest ML products from Google, and learn directly from several amazing women in the field.

During the keynote we announced:

• Simple ML for Sheets – Simple ML is an add-on, in beta, for Google Sheets from the TensorFlow team that helps make machine learning accessible to all. Anyone, even people without programming or ML expertise, can experiment and apply some of the power of machine learning to their data in Google Sheets with just a few clicks. Watch the demo here.
• MediaPipe Previews – We invited developers to preview low-code APIs that provide solutions to common on-device ML challenges across vision, natural language and audio. We also opened MediaPipe Studio, a web-based interface that provides a new way to prototype and benchmark ML solutions.
• TensorFlow Recommendation Systems Hub – We published a new dedicated page on TensorFlow.org where developers can find tools and guidance for building world-class recommendation systems with the TensorFlow ecosystem.
• Upcoming Sign Language AI Kaggle Competition – Our first Sign Language AI Competition to help the partners of deaf children learn to sign launches soon. Sign up to get notified when it launches.

Following is a quick recap, and workshops from the event. Thanks again.

Workshops:

This session gives participants a hands-on overview on how to get started in ML, covering various topics from introduction to ML models, to creating your first ML project. Learn how to use Codelabs and leverage technical documentation to help you getting started.

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TensorFlow Lite in Android with Google Play Services

TensorFlow Lite is available in Google Play services runtime for all Android devices running Play services. Learn how to run ML models without statically bundling TensorFlow Lite libraries into your app and enable you to reduce the size of your apps and gain improved performance from the latest stable version of the libraries.

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Advanced On-Device ML Made Easy with MediaPipe

Learn how MediaPipe can help you easily create custom cross-platform on-device ML solutions with low-code and no-code tools. In this session, you’ll see how to quickly try out on-device ML solutions on a web browser, then customize them in just a few lines of Python code, and easily deploy them across multiple platforms: web, Android and Python.

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Generative Adversarial Networks (GANs) and Stable Diffusion

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What's Next?