TensorFlow Extended 101: (literally) Everything you need to know

Automate the workflow to build, validate, and deploy machine learning models.

Let’s be fair, most machine learning projects tend to start with manual workflows. This is fine, and nothing to worry about.

But, at some point, you’ll want to focus on new models instead of maintaining existing ones. That’s where TensorFlow Extended (TFX) shines.

TFX will help you lift your ML workflow to the next level: An automated end-to-end pipeline that allows machine learning to scale.

This article will guide you through the lifecycle of a machine learning pipeline with TFX.

What is TensorFlow Extended (TFX)?

If you are new to TensorFlow Extended, I recommend an article from one of my colleagues, Darren who wrote a great introduction to TFX.

Tensorflow Extended (TFX) is designed to build end-to-end machine learning pipelines.

The first time I read about TFX was in 2019 (the year it was officially released to the public). Admittedly, it…