TensorFlow Metadata provides standard representations for metadata that are useful when training machine learning models with TensorFlow.
The metadata serialization formats include:
- A schema describing tabular data (e.g., tf.Examples).
- A collection of summary statistics over such datasets.
- A problem statement quantifying the objectives of a model.
The metadata may be produced by hand or automatically during input data analysis, and may be consumed for data validation, exploration, and transformation.