Speaker "Robert Crowe" Details Back



Workshop: ML in production: Getting started with TensorFlow Extended (TFX)


Putting together an ML production pipeline for training, deploying, and maintaining ML and deep learning applications is much more than just training a model. Google has taken years of experience in developing production ML pipelines and offered the open source community TensorFlow Extended (TFX), an open source version of tools and libraries that Google uses internally.
Members of the TensorFlow team at Google will outline what’s involved in creating a production ML pipeline and walks you through working code.
Who is this presentation for?
Data scientists, ML engineers, researchers, and ML ops and DevOps practitioners
Level - Intermediate
Prerequisite knowledge
Experience with machine learning, Python, and Linux
What you'll learn
Understanding of the issues and best practices for putting machine learning models and applications into production
Materials or downloads needed in advance
Laptop - Linux or MacOS (highly recommended) or Windows (optional)
Git (or Git for Windows if using Windows, which includes Git Bash)
Docker Desktop
For Windows, please make sure that you have admin permissions and can share your drive with Docker, and open ports 445, 8080, 8888, and 6006.
Min 3GB available disk space
**BEFORE** the workshop, please run: docker pull
**BEFORE** the workshop, also please run: docker pull tensorflow/serving:nightly



A recovering data scientist and TensorFlow addict, Robert has a passion for helping developers quickly learn what they need to be productive.  He's used TensorFlow since the very early days and is excited about how it's evolving quickly to become even better than it already is.  Before moving to data science Robert led software engineering teams for both large and small companies, always focusing on clean, elegant solutions to well-defined needs.  In his spare time Robert surfs, sails, and raises a family.