September 30th at 8:30 - 10:00 CET

Code Breakfast: TensorFlow Extended running on Airflow

Code Breakfast September 30th - 8:30 -10:00 CET

Register for the Code Breakfast:


Details

  • Thursday, September 30th
  • 8:30 – 10:00 CET
  • Online

What to Expect

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. Use the orchestration system like Apache Airflow or Kubeflow to execute workflows as directed acyclic graphs (DAGs) of tasks.

At the end of this workshop, you will explore the key concepts of TFX and teach you how to run TFX workflows on Airflow, hosted on the cloud. It will demonstrate the end-to-end workflow and steps how to analyze, validate and transform data, train a model, analyze and serve it.

Google TensorFlow Extended (TFX) is an end-to-end platform for deploying production ML pipelines

When you’re ready to move your models from research to production, use TFX to create and manage a production pipeline. Watch this interesting presentation in Google I/O 2019

Speakers

Julian de Ruiter

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.

roman bokeh

Roman Ivanov

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.

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