Library and standards for schema and statistics.
Project description
TensorFlow Metadata
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.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file tensorflow_metadata-0.26.0-py3-none-any.whl.
File metadata
- Download URL: tensorflow_metadata-0.26.0-py3-none-any.whl
- Upload date:
- Size: 47.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/51.0.0 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.7.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a4378048c1168ed232d664c3ec295c032743a6d3739f79b1012f64cc77184882
|
|
| MD5 |
f64ed2c5d04335a76c7dc442cf9ab8cd
|
|
| BLAKE2b-256 |
568f4d28679c1c23237de615661d5d2961b9c79114f1a00b4daf3ccc451585f3
|
