TensorFlow Extended
TensorFlow Extended (TFX) is an end-to-end platform for deploying production machine learning pipelines. It provides a framework for orchestrating ML workflows, including data validation, transformation, training, evaluation, and serving. TFX is built on TensorFlow and is designed to bring best practices for ML productionization, such as data versioning, model monitoring, and reproducibility.
Developers should learn TFX when building scalable, reliable ML systems that require automated pipelines for continuous training and deployment. It is particularly useful for teams implementing MLOps practices, handling large datasets, or needing to maintain models in production with minimal manual intervention. Use cases include recommendation systems, fraud detection, and any application where model updates must be frequent and data-driven.