Key concepts of TensorFlow Extended (TFX) and develop the skills to run TFX workflows on Apache Airflow
In this workshop, we’ll dive into TFX, a tool built for consistent and reliable deployment of TensorFlow-based models to production. In practice, this means that TFX allows you to follow MLOps best practices with model versioning, data validation, metadata management, performance monitoring, serving and more. For this session, we’ll explore the key concepts of TFX and teach you how to run TFX workflows on Airflow.
Program (Thursday 30/9)
8:30– 10:00 CET – Online event
Speakers: Roman Ivanov and Julian de Ruiter
Roman is a Machine Learning Engineer who brings Data and AI solutions to production. With more than 10 years of industry experience in software and data engineering at companies like UBS Bank (CH), Citigroup Bank (US) and XITE Music TV (NL).
Among the favourite technologies are Apache Spark, TensorFlow, ScikitLearn, Python, Scala, Golang, SQL, Bash, Kubernetes and Docker.
Julian de Ruiter
Julian is a machine learning engineer at GoDataDriven, who also enjoys dabbling in developing open source software. He previously studied at the Delft University of Technology, where he completed his Bachelor in Computer Science and his Master in Bioinformatics cum laude.
After Delft, he spent his PhD exploring breast cancer development and origins of (acquired) treatment resistance at the Netherlands Cancer institute, after which it made sense for Julian to use his skills in a more applied setting at GoDataDriven.