TensorFlow in production: TF Extended, TF Hub, and TF Serving (Google I/O '18)

This session will introduce TensorFlow Extended (TFX), TensorFlow Hub, and announce new innovations and features in TensorFlow Serving. As machine learning is evolving from experimentation to serve production workloads, so does the need to effectively manage the end-to-end training and production workflow including model management, versioning, and serving. TFX provides this solution to Google and you'll hear about the release plans to deliver it to the community. TensorFlow Hub is a central repository of reusable parts of TensorFlow models. With its libraries, you can incorporate these parts in your models for transfer learning and package them up to be served with TensorFlow Serving. Rate this session by signing-in on the I/O website here → https://goo.gl/g6f9KH Watch more TensorFlow sessions from I/O '18 here → https://goo.gl/GaAnBR See all the sessions from Google I/O '18 here → https://goo.gl/q1Tr8x Subscribe to the TensorFlow channel → https://goo.gl/ht3WGe #io18 event: Google I/O 2018; re_ty: Publish; product: TensorFlow - TensorFlow Extended, TensorFlow - TensorFlow Hub; fullname: Jeremiah Harmsen, Andrew Gasparovic, James Pine; event: Google I/O 2018;