Machine Learning Systems Pt. 2: Data Pipelines with TensorFlow Extended

In part 1, I covered an overview and some of the primary challenges in doing MLOps. Implementing models at scale can be a difficult exercise due to the changing nature of data, business, and code. In this part, I'll show how you can build data pipeline components using TensorFlow Extended (TFX). This will follow the work and skills taught in the Machine Learning Engineering (MLOps) in Production Specialization by DeepLearning.ai, I'll go through the final assignment here, but I'll be applying it to a new dataset.