TensorFlow Extended (TFX) is a TensorFlow-based general-purpose machine learning platform implemented at Google
Project description
TFX
TensorFlow Extended (TFX) is a TensorFlow-based general-purpose machine learning platform implemented at Google. We’ve open sourced some of the TFX libraries listed below. The TFX repository will contain horizontal components that integrate these libraries in one platform. For now, it will include examples of how to use the already open sourced TFX libraries together.
Examples
Available TFX libraries
TensorFlow Data Validation
A library for exploring and validating machine learning data.
TensorFlow Transform
A preprocessing pipeline to perform full-pass analyze phases over data to create transformation graphs that are consistently applied during training and serving.
TensorFlow Model Analysis
Libraries and visualization components to compute full-pass and sliced model metrics over large datasets, and analyze them in a notebook.
TensorFlow Serving
A flexible, high-performance serving system for machine learning models, designed for production environments.
Compatible versions
- ml-metadata
The following table describes how the tfx package versions are compatible
with its major dependency Pypi packages. This is determined by our testing
framework, but other untested combinations may also work.
| tfx | tensorflow | apache-beam[gcp] | tensorflow-data-validation | tensorflow-model-analysis | tensorflow-transform | ml-metadata | tensorflow-metadata |
|---|---|---|---|---|---|---|---|
| GitHub master | nightly (1.x) | 2.10.0 | 0.12.0 | 0.12.1 | 0.12.0 | 0.13.1 | 0.12.1 |
Release history Release notifications | RSS feed
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