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.
How it works
A TFX pipeline is a sequence of components that implement an ML pipeline which is specifically designed for scalable, high-performance machine learning tasks. Components are built using TFX libraries which can also be used individually.
How companies are using TFX
Solutions to common problems
Explore step-by-step tutorials to help you with your projects.
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This guide trains a neural network model to classify images of clothing, like sneakers and shirts, saves the trained model, and then serves it with TensorFlow Serving. The focus is on TensorFlow Serving, rather than the modeling and training in TensorFlow.
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An introduction to TFX and Cloud AI Platform Pipelines to create your own machine learning pipelines on Google Cloud. Follow a typical ML development process, starting by examining the dataset, and ending up with a complete working pipeline.
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Learn how TFX can create and evaluate machine learning models that will be deployed on-device. TFX now provides native support for TFLite, which makes it possible to perform highly efficient inference on mobile devices.
News & announcements
Check out our blog and YouTube playlist for additional TFX content,
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Simulated Spotify Listening Experiences for Reinforcement Learning with TensorFlow and TF-Agents
Many of our music recommendation problems involve providing users with ordered sets of items that satisfy users’ listening preferences and intent at that point in time. We base current recommendations on previous interactions with our application
TensorFlow
October 19, 2023
Serving With TF and GKE: Stable Diffusion
Generative AI models like Stable Diffusion 1 that lets anyone generate high-quality images from natural language text prompts enable different use cases across different industries. These types of models allow people to generate these images not only
TensorFlow
April 28, 2023
How Vodafone Uses TensorFlow Data Validation in their Data Contracts to Elevate Data Governance at Scale
As one of the largest telecommunications companies worldwide, Vodafone is working with Google Cloud to advance their entire data landscape, including their data lake, data warehouse (DWH), and in particular AI/ML strategies. While Vodafone has used
TensorFlow
March 10, 2023
Extend your TFX pipeline with TFX-Addons
To produce production-level machine learning models, TensorFlow provides a portfolio of libraries under the umbrella of TensorFlow Extended (TFX). With just a pip install, TFX already includes a number of versatile pipeline components - referred to
TensorFlow
February 7, 2023